Special Issue "Applied Econometrics"

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

Deadline for manuscript submissions: closed (31 December 2018).

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Special Issue Editor

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

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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 (14 papers)

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Research

Open AccessArticle
Abnormal Returns or Mismeasured Risk? Network Effects and Risk Spillover in Stock Returns
J. Risk Financial Manag. 2019, 12(2), 50; https://doi.org/10.3390/jrfm12020050 - 29 Mar 2019
Cited by 1
Abstract
Recent event study literature has highlighted abnormal stock returns, particularly in short event windows. A common explanation is the cross-correlation of stock returns that are often enhanced during periods of sharp market movements. This suggests the misspecification of the underlying factor model, typically [...] Read more.
Recent event study literature has highlighted abnormal stock returns, particularly in short event windows. A common explanation is the cross-correlation of stock returns that are often enhanced during periods of sharp market movements. This suggests the misspecification of the underlying factor model, typically the Fama-French model. By drawing upon recent panel data literature with cross-section dependence, we argue that the Fame-French factor model can be enriched by allowing explicitly for network effects between stock returns. We show that recent empirical work is consistent with the above interpretation, and we advance some hypotheses along which new structural models for stock returns may be developed. Applied to data on stock returns for the 30 Dow Jones Industrial Average (DJIA) stocks, our framework provides exciting new insights. Full article
(This article belongs to the Special Issue Applied Econometrics) Printed Edition available
Open AccessArticle
Effects of Global Oil Price on Exchange Rate, Trade Balance, and Reserves in Nigeria: A Frequency Domain Causality Approach
J. Risk Financial Manag. 2019, 12(1), 43; https://doi.org/10.3390/jrfm12010043 - 13 Mar 2019
Cited by 2
Abstract
This study investigated the relative Granger causal effects of oil price on exchange rate, trade balance, and foreign reserve in Nigeria. We used seasonally adjusted quarterly data from 1986Q4 to 2018Q1 to remove predictable changes in the series. Given the non-stationarity of our [...] Read more.
This study investigated the relative Granger causal effects of oil price on exchange rate, trade balance, and foreign reserve in Nigeria. We used seasonally adjusted quarterly data from 1986Q4 to 2018Q1 to remove predictable changes in the series. Given the non-stationarity of our variables, we found cointegration to exist only between oil price and foreign reserve. The presence of cointegration implied the existence of long run relationship between the variables. The Granger causality result showed that oil price strongly Granger caused foreign reserve in the short period. However, no Granger causal relationships were found between oil price and trade balance and for oil price and exchange rate. The implication of the result is that Nigerian government should not rely solely on oil price to sustain her reserve but to diversify the economy towards non-resource production and export for foreign exchange generation. Full article
(This article belongs to the Special Issue Applied Econometrics) Printed Edition available
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Open AccessArticle
What Factors Affect Income Inequality and Economic Growth in Middle-Income Countries?
J. Risk Financial Manag. 2019, 12(1), 40; https://doi.org/10.3390/jrfm12010040 - 08 Mar 2019
Cited by 3
Abstract
Income inequality in many middle-income countries has increased at an alarming level. While the time series relationship between income inequality and economic growth has been extensively investigated, the causal and dynamic link between them, particularly for the middle-income countries, has been largely ignored [...] Read more.
Income inequality in many middle-income countries has increased at an alarming level. While the time series relationship between income inequality and economic growth has been extensively investigated, the causal and dynamic link between them, particularly for the middle-income countries, has been largely ignored in the current literature. This study was conducted to fill in this gap on two different samples for the period from 1960 to 2014: (i) a full sample of 158 countries; and (ii) a sample of 86 middle-income countries. The Granger causality test and a system generalized method of moments (GMM) are utilized in this study. The findings from this study indicate that causality is found from economic growth to income inequality and vice versa in both samples of countries. In addition, this study also finds that income inequality contributes negatively to the economic growth in the middle-income countries in the research period. Full article
(This article belongs to the Special Issue Applied Econometrics) Printed Edition available
Open AccessArticle
The Importance of the Financial Derivatives Markets to Economic Development in the World’s Four Major Economies
J. Risk Financial Manag. 2019, 12(1), 35; https://doi.org/10.3390/jrfm12010035 - 14 Feb 2019
Cited by 8
Abstract
Over the past three decades, China and India have attained economic power close to that of Japan and the U.S. During this period, the importance of the derivatives market within the financial market has been widely recognized. However, little supporting evidence is available [...] Read more.
Over the past three decades, China and India have attained economic power close to that of Japan and the U.S. During this period, the importance of the derivatives market within the financial market has been widely recognized. However, little supporting evidence is available on its economic effects. This paper investigates the dynamic relationship between the derivatives markets and economic development in these four large economies, which we consider together as the CIJU (China, India, Japan, and the U.S.) group. We use a Granger-causality test in the framework of a vector error correction model (VECM) to examine this causal and dynamic relation with data for the period 1998Q1 to 2017Q4. Derivative markets are found to positively contribute to economic development in the short run in the U.S., Japan, and India, but the effect disappears in the long run. In China, the derivatives market has a negative effect on economic development in the short run. However, in the long run, we observe a positive effect from the derivatives market on economic development based on two long-run estimation techniques, namely, dynamic ordinary least squares and fully modified ordinary least squares. Also, the development of derivative markets causes growth volatility in India, both in the short run and long run. Full article
(This article belongs to the Special Issue Applied Econometrics) Printed Edition available
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Open AccessArticle
Multivariate Student versus Multivariate Gaussian Regression Models with Application to Finance
J. Risk Financial Manag. 2019, 12(1), 28; https://doi.org/10.3390/jrfm12010028 - 09 Feb 2019
Abstract
To model multivariate, possibly heavy-tailed data, we compare the multivariate normal model (N) with two versions of the multivariate Student model: the independent multivariate Student (IT) and the uncorrelated multivariate Student (UT). After recalling some facts about these distributions and models, known but [...] Read more.
To model multivariate, possibly heavy-tailed data, we compare the multivariate normal model (N) with two versions of the multivariate Student model: the independent multivariate Student (IT) and the uncorrelated multivariate Student (UT). After recalling some facts about these distributions and models, known but scattered in the literature, we prove that the maximum likelihood estimator of the covariance matrix in the UT model is asymptotically biased and propose an unbiased version. We provide implementation details for an iterative reweighted algorithm to compute the maximum likelihood estimators of the parameters of the IT model. We present a simulation study to compare the bias and root mean squared error of the ensuing estimators of the regression coefficients and covariance matrix under several scenarios of the potential data-generating process, misspecified or not. We propose a graphical tool and a test based on the Mahalanobis distance to guide the choice between the competing models. We also present an application to model vectors of financial assets returns. Full article
(This article belongs to the Special Issue Applied Econometrics) Printed Edition available
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Open AccessArticle
Does the Misery Index Influence a U.S. President’s Political Re-Election Prospects?
J. Risk Financial Manag. 2019, 12(1), 22; https://doi.org/10.3390/jrfm12010022 - 01 Feb 2019
Cited by 1
Abstract
We seek to determine whether a United States President’s job approval rating is influenced by the Misery Index. This hypothesis is examined in two ways. First, we employ a nonlinear model that includes several macroeconomic variables: the current account deficit, exchange rate, unemployment, [...] Read more.
We seek to determine whether a United States President’s job approval rating is influenced by the Misery Index. This hypothesis is examined in two ways. First, we employ a nonlinear model that includes several macroeconomic variables: the current account deficit, exchange rate, unemployment, inflation, and mortgage rates. Second, we employ probit and logit regression models to calculate the probabilities of U.S. Presidents’ approval ratings to the Misery Index. The results suggest that Layton’s model does not perform well when adopted for the United States. Conversely, the probit and logit regression analysis suggests that the Misery Index significantly impacts the probability of the approval of U.S. Presidents’ performances. Full article
(This article belongs to the Special Issue Applied Econometrics) Printed Edition available
Open AccessArticle
Limitation of Financial Health Prediction in Companies from Post-Communist Countries
J. Risk Financial Manag. 2019, 12(1), 15; https://doi.org/10.3390/jrfm12010015 - 18 Jan 2019
Cited by 3
Abstract
The financial health of a company can be seen as the ability to maintain a balance against changing conditions in the environment and at the same time in relation to everyone participating in the business. In the evaluation of financial health and prediction [...] Read more.
The financial health of a company can be seen as the ability to maintain a balance against changing conditions in the environment and at the same time in relation to everyone participating in the business. In the evaluation of financial health and prediction of financial problems of the companies, various indexes are used that can serve as input for expert estimation or creation of various models using, for example, multi-dimensional statistical methods. The practical application of the proper method for evaluation of financial health has been analysed in post-communist countries, since they have common historic experiences and economic interests. During the research we followed up the following indexes: Altman model, Taffler model, Springate model, and the index IN, based on multi-dimensional discrimination analysis. From the research results there is obvious a necessity to combine available methods in post-communist countries and at least to eliminate their disadvantages partially. Experiences from prediction models have proved their relatively high prediction ability, but only in perfect conditions, which cannot be affirmed in post-communist countries. The task remains to modify existing indexes to concrete situations and problems of the individual industries in the chosen countries, which have unique conditions for business making. Full article
(This article belongs to the Special Issue Applied Econometrics) Printed Edition available
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Open AccessShort Note
Cash Use of the Taiwan Dollar: Is It Efficient?
J. Risk Financial Manag. 2019, 12(1), 13; https://doi.org/10.3390/jrfm12010013 - 15 Jan 2019
Cited by 1
Abstract
Two banknotes and two coins of the New Taiwan Dollar are infrequently (if at all) used in Taiwan when people make cash payments. This note examines the effect of this behavior on the efficiency of cash payments. The results are compared with the [...] Read more.
Two banknotes and two coins of the New Taiwan Dollar are infrequently (if at all) used in Taiwan when people make cash payments. This note examines the effect of this behavior on the efficiency of cash payments. The results are compared with the Euro, where the two highest and two lowest tokens are also rarely used. We find for Taiwan that inefficiency increases with 60.7%, while for the Euro it is only 25.3%. The main reason is that two of the rarely used coins and notes in Taiwan are in the middle of the denominational range, whereas for the Euro, these tokens concern the ends of that range. Full article
(This article belongs to the Special Issue Applied Econometrics) Printed Edition available
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 - 22 Nov 2018
Cited by 7
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 [...] Read more.
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) Printed Edition available
Open AccessArticle
Systemic Approach to Management Control through Determining Factors
J. Risk Financial Manag. 2018, 11(4), 65; https://doi.org/10.3390/jrfm11040065 - 22 Oct 2018
Cited by 1
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 [...] Read more.
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) Printed Edition available
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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 - 06 Jul 2018
Cited by 1
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 [...] Read more.
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) Printed Edition available
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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 - 01 Jul 2018
Cited by 1
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 [...] Read more.
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) Printed Edition available
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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 - 28 Dec 2017
Cited by 1
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 [...] Read more.
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) Printed Edition available
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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 - 14 Nov 2017
Cited by 1
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 [...] Read more.
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) Printed Edition available
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