Special Issue "Applied Econometrics"

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074).

Deadline for manuscript submissions: 31 December 2018

Special Issue Editor

Guest Editor
Prof. Dr. Chia-Lin Chang

Department of Applied Economics and Department of Finance, National Chung Hsing University, 145 Xingda Road, Taichung 40227, Taiwan
Website | E-Mail
Interests: applied econometrics; financial econometrics; energy finance; time series analysis; forecasting; empirical industrial organisation; risk management

Special Issue Information

Dear Colleagues,

This Special Issue is concerned with the broad topic of Applied Econometrics, and includes any novel theoretical or empirical research associated with the application of econometrics.

Theoretical contributions should be associated with an empirical example, or directions in which the novel ideas might be applied.

The Special Issue may be associated with any contributions in: Theoretical and applied econometrics; economics; theoretical and applied financial econometrics; quantitative finance; risk; financial management; theoretical and applied statistics; time series analysis; forecasting; mathematics; energy economics; energy finance; agricultural economics; informatics; data mining; bibliometrics; and international rankings of journals and academics.

Distinguished Prof. Dr. Chia-Lin Chang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 350 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • theoretical and applied econometrics
  • economics
  • theoretical and applied financial econometrics
  • quantitative finance
  • risk
  • financial management
  • theoretical and applied statistics
  • time series analysis
  • forecasting
  • mathematics
  • energy economics
  • energy finance
  • agricultural economics
  • informatics
  • data mining
  • bibliometrics
  • international rankings of journals and academics.

Published Papers (8 papers)

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Research

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Open AccessArticle The Relationship between Economic Freedom and FDI versus Economic Growth: Evidence from the GCC Countries
J. Risk Financial Manag. 2018, 11(4), 81; https://doi.org/10.3390/jrfm11040081
Received: 6 November 2018 / Revised: 16 November 2018 / Accepted: 18 November 2018 / Published: 22 November 2018
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Abstract
This study aims to explain the role of economic freedom in attracting foreign investments and thus raising the level of economic growth. Through a study based on a sample composed of the Gulf Cooperation Council (GCC) countries. A standard model consisting of GCC
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This study aims to explain the role of economic freedom in attracting foreign investments and thus raising the level of economic growth. Through a study based on a sample composed of the Gulf Cooperation Council (GCC) countries. A standard model consisting of GCC countries (Saudi Arabia, United Arab Emirates, Qatar, Kuwait, and Oman) was used during the period from 1995 to 2017. We based on the analytical descriptive and secondly, we used a multivariate analysis based on the panel unit root test, the cointegration and finally the regression Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) following the existence of a long-term integration, which includes the modern standard methods to determine the role of economic freedom in raising foreign direct investment and thus economic growth in the second stage. The research findings from GCC countries support the literature, suggesting that there are indeed some indications that greater levels of economic freedom support higher rates of economic growth in a country. Full article
(This article belongs to the Special Issue Applied Econometrics)
Open AccessArticle Systemic Approach to Management Control through Determining Factors
J. Risk Financial Manag. 2018, 11(4), 65; https://doi.org/10.3390/jrfm11040065
Received: 28 September 2018 / Revised: 11 October 2018 / Accepted: 17 October 2018 / Published: 22 October 2018
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Abstract
This article aimed to analyse the influence of the main factors on management control used in optimization activities, in order to reach the strategic goals of a company. Agency, transactional costs and contingency theories have been analysed from the traditional perspective. This study
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This article aimed to analyse the influence of the main factors on management control used in optimization activities, in order to reach the strategic goals of a company. Agency, transactional costs and contingency theories have been analysed from the traditional perspective. This study reviewed resource-based, institutional, planned behaviour and upper echelon theories, and underlined the main features of management control processes. Empirical evaluation was conducted using data collected from interviews of top management of the main and secondary segments of the Bucharest Stock Exchange. Consequently, we showed the specific features of the systemic approach to management control by means of its determining factors: control environment, management strategies and budgetary system, operational control and the performance appraisal system. Full article
(This article belongs to the Special Issue Applied Econometrics)
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Open AccessArticle Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK
J. Risk Financial Manag. 2018, 11(4), 58; https://doi.org/10.3390/jrfm11040058
Received: 17 August 2018 / Revised: 23 September 2018 / Accepted: 28 September 2018 / Published: 29 September 2018
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Abstract
As stock market indexes are not tradeable, the importance and trading volume of Exchange-Traded Funds (ETFs) cannot be understated. ETFs track and attempt to replicate the performance of a specific index. Numerous studies have demonstrated a strong relationship between the S&P500 Composite Index
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As stock market indexes are not tradeable, the importance and trading volume of Exchange-Traded Funds (ETFs) cannot be understated. ETFs track and attempt to replicate the performance of a specific index. Numerous studies have demonstrated a strong relationship between the S&P500 Composite Index and the Volatility Index (VIX), but few empirical studies have focused on the relationship between VIX and ETF returns. The purpose of the paper is to investigate whether VIX returns affect ETF returns by using vector autoregressive (VAR) models to determine whether daily VIX returns with different moving average processes affect ETF returns. The ARCH-LM test shows conditional heteroskedasticity in the estimation of ETF returns, so that the Diagonal BEKK (named after Baba, Engle, Kraft and Kroner) model is used to accommodate multivariate conditional heteroskedasticity in the VAR estimates of ETF returns. Daily data on ETF returns that follow different stock indexes in the USA and Europe are used in the empirical analysis, which is presented for the full data set, as well as for the three sub-periods Before, During, and After the Global Financial Crisis. The estimates show that daily VIX returns have: (1) significant negative effects on European ETF returns in the short run; (2) stronger significant effects on single-market ETF returns than on European ETF returns; and (3) lower impacts on the European ETF returns than on S&P500 returns. For the European markets, the estimates of the mean equations tend to differ between the whole sample period and the sub-periods, but the estimates of the matrices A and B in the Diagonal BEKK model are quite similar for the whole sample period and at least two of the three sub-periods. For the US Markets, the estimates of the mean equations also tend to differ between the whole sample period and the sub-periods, but the estimates of the matrices A and B in the Diagonal BEKK model are very similar for the whole sample period and the three sub-periods. Full article
(This article belongs to the Special Issue Applied Econometrics)
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Open AccessArticle Nonlinear Time Series Modeling: A Unified Perspective, Algorithm and Application
J. Risk Financial Manag. 2018, 11(3), 37; https://doi.org/10.3390/jrfm11030037
Received: 4 June 2018 / Accepted: 3 July 2018 / Published: 6 July 2018
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Abstract
A new comprehensive approach to nonlinear time series analysis and modeling is developed in the present paper. We introduce novel data-specific mid-distribution-based Legendre Polynomial (LP)-like nonlinear transformations of the original time series {Y(t)} that enable us to adapt
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A new comprehensive approach to nonlinear time series analysis and modeling is developed in the present paper. We introduce novel data-specific mid-distribution-based Legendre Polynomial (LP)-like nonlinear transformations of the original time series {Y(t)} that enable us to adapt all the existing stationary linear Gaussian time series modeling strategies and make them applicable to non-Gaussian and nonlinear processes in a robust fashion. The emphasis of the present paper is on empirical time series modeling via the algorithm LPTime. We demonstrate the effectiveness of our theoretical framework using daily S&P 500 return data between 2 January 1963 and 31 December 2009. Our proposed LPTime algorithm systematically discovers all the ‘stylized facts’ of the financial time series automatically, all at once, which were previously noted by many researchers one at a time. Full article
(This article belongs to the Special Issue Applied Econometrics)
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Open AccessFeature PaperArticle How Informative Are Earnings Forecasts?
J. Risk Financial Manag. 2018, 11(3), 36; https://doi.org/10.3390/jrfm11030036
Received: 28 May 2018 / Revised: 22 June 2018 / Accepted: 26 June 2018 / Published: 1 July 2018
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Abstract
We constructed forecasts of earnings forecasts using data on 406 firms and forecasts made by 5419 individuals with on average 25 forecasts per individual. We verified previously found predictors, which are the average of the most recent available forecast for each forecaster and
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We constructed forecasts of earnings forecasts using data on 406 firms and forecasts made by 5419 individuals with on average 25 forecasts per individual. We verified previously found predictors, which are the average of the most recent available forecast for each forecaster and the difference between the average and the forecast that this forecaster previously made. We extended the knowledge base by analyzing the unpredictable component of the earnings forecast. We found that for some forecasters the unpredictable component can be used to improve upon the predictable forecast, but we also found that this property is not persistent over time. Hence, a user of the forecasts cannot trust that the forecaster will remain to be of forecasting value. We found that, in general, the larger is the unpredictable component, the larger is the forecast error, while small unpredictable components can lead to gains in forecast accuracy. Based on our results, we formulate the following practical guidelines for investors: (i) for earnings analysts themselves, it seems to be the safest to not make large adjustments to the predictable forecast, unless one is very confident about the additional information; and (ii) for users of earnings forecasts, it seems best to only use those forecasts that do not differ much from their predicted values. Full article
(This article belongs to the Special Issue Applied Econometrics)
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Open AccessArticle FHA Loans in Foreclosure Proceedings: Distinguishing Sources of Interdependence in Competing Risks
J. Risk Financial Manag. 2018, 11(1), 2; https://doi.org/10.3390/jrfm11010002
Received: 31 October 2017 / Revised: 15 December 2017 / Accepted: 18 December 2017 / Published: 28 December 2017
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Abstract
A mortgage borrower has several options once a foreclosure proceedings is initiated, mainly default and prepayment. Using a sample of FHA mortgage loans, we develop a dependent competing risks framework to examine the determinants of time to default and time to prepayment once
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A mortgage borrower has several options once a foreclosure proceedings is initiated, mainly default and prepayment. Using a sample of FHA mortgage loans, we develop a dependent competing risks framework to examine the determinants of time to default and time to prepayment once the foreclosure proceedings is initiated. More importantly, we examine the interdependence between default and prepayment, through both the correlation of the unobserved heterogeneity terms and the preventive behavior of the individual mortgage borrowers. We find that time to default and time to prepayment are affected by several factors, such as the Loan-To-Value ratio (LTV), FICO score and unemployment rate. In addition, we find strong evidence that supports the existence of interdependence between the default and prepayment hazards through both the correlation of the unobserved heterogeneity terms and the preventive behavior of individual mortgage borrowers. We show that neglecting the interdependence through the preventive behavior of the individual mortgage borrowers can lead to biased estimates and misleading inference. Full article
(This article belongs to the Special Issue Applied Econometrics)
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Open AccessFeature PaperArticle Recovering Historical Inflation Data from Postage Stamps Prices
J. Risk Financial Manag. 2017, 10(4), 21; https://doi.org/10.3390/jrfm10040021
Received: 17 October 2017 / Revised: 7 November 2017 / Accepted: 9 November 2017 / Published: 14 November 2017
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Abstract
For many developing countries, historical inflation figures are rarely available. We propose a simple method that aims to recover such figures of inflation using prices of postage stamps issued in earlier years. We illustrate our method for Suriname, where annual inflation rates are
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For many developing countries, historical inflation figures are rarely available. We propose a simple method that aims to recover such figures of inflation using prices of postage stamps issued in earlier years. We illustrate our method for Suriname, where annual inflation rates are available for 1961 until 2015, and where fluctuations in inflation rates are prominent. We estimate the inflation rates for the sample 1873 to 1960. Our main finding is that high inflation periods usually last no longer than 2 or 3 years. An Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) model for the recent sample and for the full sample with the recovered inflation rates shows the relevance of adding the recovered data. Full article
(This article belongs to the Special Issue Applied Econometrics)
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Review

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Open AccessFeature PaperReview Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections
J. Risk Financial Manag. 2018, 11(1), 15; https://doi.org/10.3390/jrfm11010015
Received: 4 February 2018 / Revised: 7 March 2018 / Accepted: 13 March 2018 / Published: 20 March 2018
Cited by 1 | PDF Full-text (435 KB) | HTML Full-text | XML Full-text
Abstract
The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses research issues that are related to the various disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to
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The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses research issues that are related to the various disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models, as well as conduct simulation to examine whether the estimators in their theories on estimation and hypothesis testing have good size and high power. Thereafter, academics and practitioners could apply theory to analyse some interesting issues in the seven disciplines and cognate areas. Full article
(This article belongs to the Special Issue Applied Econometrics)
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