Forthcoming articles


International Journal of Computational Economics and Econometrics


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International Journal of Computational Economics and Econometrics (30 papers in press)


Regular Issues


  • Beyond Equilibrium: Revisiting Two-Sided Markets from an Agent-Based Modeling Perspective   Order a copy of this article
    by Torsten Heinrich, Claudius Grabner 
    Abstract: Two-sided markets are an important aspect of today's economies. Yet, the attention they have received in economic theory is limited, mainly due to methodological constraints of conventional approaches: two-sided markets quickly lead to non-trivial dynamics that would require a computational approach, as analytical models quickly become intractable. One approach to this problem is to opt for models that operate on an aggregated level, abstracting from most of the (micro-level) causes of these non-trivial dynamics. Here we revisit a well-known equilibrium model by Rochet and Tirole of two-sided markets that has taken this approach. Analyzing the model from an agent-based perspective, however, reveals several inconsistencies and implicit assumptions of the original model. This, together with the highly implausible assumptions that are required to make the model analytically tractable, limits its explanatory power significantly and motivates an alternative approach. The agent-based model we propose allows us to study the phenomenon of two-sided markets in a more realistic and adequate manner: Not only are we able to compare different decision making rules for the providers, we are also able to study situations with more than two providers. Thus, our model represents a first step towards a more realistic and policy-relevant study of two-sided markets.
    Keywords: two-sided markets; network externalities; agent-based modelling; simulation; heuristic decision making; reinforcement learning; satisīŦcing; differential evolution; evolutionary economics; market structure; IT economics; equilibrium dynamics.
    DOI: 10.1504/IJCEE.2019.10016573
  • Gender dimension of migration decisions in Ghana: The reinforcing role of anticipated welfare of climatic effect   Order a copy of this article
    by Franklin Amuakwa-Mensah, Victoria N. Sam, Evelyne Nyathira Kihiu 
    Abstract: The concept of migration has been a male phenomenon in time past, however, there has been a change in events as females are gradually gaining dominance in migration patterns in recent times. Using nationwide survey data this paper investigates the determinants of internal migration decisions for males and females in Ghana. We examined whether there is any significant differences in how climate elements together with anticipated welfare gains and socio-economic factors explain internal migration decision of males and females. We find some variations in the determinants of migration decisions for males and female, though these decisions are significantly affected by anticipated welfare gain, socio-economic factors and climate conditions. We observed that females respond more to climate or environmental elements than males. Moreover, the effect of climate on migration decisions for both males and females is reinforced by anticipated welfare gain.
    Keywords: Climate; environment; males; females; migration; Heckman two-stage; Ghana.

  • Insurance risk capital and risk aggregation: Bivariate copula approach   Order a copy of this article
    by Hanene Mejdoub, Mounira BEN ARAB 
    Abstract: The current paper discusses the risk aggregation issue using copula theory in the sphere of the insurance industry. In this context, a flexible modelling of the dependence structure for non-life insurance risks is considered. The aim of the modelling is to assess the impact of dependence structure among losses on the total risk capital estimation measured by the Value-at-Risk. Using numerical illustrations based on a Tunisian insurance company, we use first various copula families that can capture the dependencies across losses that are derived from four lines of business. To obtain the appropriate bivariate copula, we perform a goodness-of-fit analysis. Then, based on the Monte-Carlo simulation, the total risk capital is deduced by applying the Value at risk on the aggregate loss distributions. We also conduct a comparative analysis between the various types of the copulas. Our findings reveal that there is a regular impact on the capital requirement estimation indicating that a static approach ignoring the real dependencies between different risks can systematically lead to an overestimation of the total capital requirement.
    Keywords: Non-life insurance; Risk aggregation; Value-at-Risk; Dependence structure; Bivariate Copulas; Monte-Carlo Simulation.

  • Research Note: Futures Hedging with Stochastic Volatility: A New Method   Order a copy of this article
    by Moawia Alghalith, Christos Floros 
    Abstract: The aim of this paper is to present a continuous-time dynamic model of futures hedging. In particular, we extend the theoretical and empirical literature (e.g. Alghalith, 2016; Alghalith et al., 2015; and Corsi et al., 2008) in several important ways. First, we present a theory-based model. A significant empirical contribution is that we do not need data for the basis risk or the spot price. To the best of our knowledge, this is the first paper to assume that the volatility of futures price is stochastic and thus to estimate the volatility of volatility of futures price. Using daily futures data from the S&P500 index, we calculate an average daily volatility as well as the volatility of volatility of futures prices. We recommend that the managers of the futures market should report the stochastic volatility of the futures price (and its volatility), in addition to the traditional volatility.
    Keywords: stochastic volatility; volatility of volatility; futures; hedging.

  • Earnings Management to Avoid Losses and Earnings Declines in Croatia   Order a copy of this article
    by Stavros Degiannakis, George Giannopoulos, Salma Ibrahim, Ivana Rozic 
    Abstract: This paper provides empirical evidence that Croatian companies manage reported earnings to avoid losses and earnings declines. Specifically, we find that the cross-sectional distribution of scaled earnings and changes in earnings show high frequencies of small positive earnings and small increases in earnings while the frequencies of small losses and small decreases in earnings are less frequent. Furthermore, we demonstrate that these discontinuities are likely due to discretionary accruals. We examine the frequency distribution of reported earnings after removing discretionary accruals and find that the cross sectional distributions of non-discretionary scaled earnings shows lower frequencies of small positive earnings and higher frequencies of small negative earnings. Additionally, the cross sectional distribution of non-discretionary change in earnings demonstrates mixed frequencies of non-discretionary changes in earnings. Overall, this paper adds new empirical evidence to the benchmark-beating literature by demonstrating international evidence of earnings management around zero earnings and zero earnings changes benchmarks.
    Keywords: Earnings management; Earnings Declines; Earnings Losses; Discretionary Accruals; Earnings frequency distribution.

  • Stein-Rule Estimation in Genetic Carrier Testing   Order a copy of this article
    by Tong Zeng, Carter Hill 
    Abstract: In this paper, we apply the fully correlated random parameters logit (FCRPL) model to the genetic carrier testing data using shrinkage estimation. We show that shrinkage estimates with higher shrinkage constant improve the percentages of correct predicted choices by 2% and 10% respectively with Jewish and general population samples. The mean estimates of elasticity based on the shrinkage estimates are closer to those with the FCRPL model estimates and have smaller standard errors than the corresponding results based on the uncorrelated random parameters logit model estimates.
    Keywords: pretest estimator; positive-part Stein-like estimator; likelihood ratio test; random parameters logit model.
    DOI: 10.1504/IJCEE.2019.10016587
  • Efficiency in Banking: Does the Choice of Inputs and Outputs Matter?   Order a copy of this article
    by Christos Floros, Constantin Zopounidis, Christos Lemonakis, Alexandros Garefalakis 
    Abstract: This paper examines banking efficiency using recent data from PIGS countries (i.e.: Portugal, Italy, Greece and Spain) which suffer from debt problems. We employ a 2-stage approach based on the effect of several items of balance sheets on cash flows and DEA analysis. More specifically, we extend previous studies by giving attention to the deposit dilemma. The reported results show that the choice of inputs and outputs does matter in the case of European banking efficiency. Although the role of deposits is controversial, we find that deposits may be an output variable, due to liquidity issues that play a major role in the efficiency of PIGS banking sector. We also report that the DEA model with deposits as an output variable generates efficiency scores that fall between periods. These results are helpful to bank managers and financial analysts dealing with efficiency modelling.
    Keywords: PIGS; Banking sector; Efficiency; Deposits dilemma; 2-stage approach; Cash flows; DEA; regression.

  • Multi-period Mean-variance Portfolio Selection with Practical Constraints Using Heuristic Genetic Algorithms   Order a copy of this article
    by Yao-Tsung Chen, Hao-Qun Yang 
    Abstract: Since Markowitz proposed the meanvariance (MV) formulation in 1952, it has been used to configure various portfolio selection problems. However Markowitzs solution is only for a single period. Multi-period portfolio selection problems have been studied for a long time but most solutions depend on various forms of utility function, which are unfamiliar to general investors. Some works have formulated the problems as MV models and solved them analytically in closed form subject to certain assumptions. Unlike analytical solutions, genetic algorithms (GA) are more flexible because they can solve problems without restrictive assumptions. The purpose of this paper is to formulate multi-period portfolio selection problems as MV models and solve them by GA. To illustrate the generality of our algorithm, we implement a program by Microsoft Visual Studio to solve a multi-period portfolio selection problem for which there exists no general analytical solution.
    Keywords: Multi-period portfolio selection; Mean-variance formulation; Genetic algorithm; Transaction costs.

  • Using singular spectrum analysis for inference on seasonal time series with seasonal unit roots   Order a copy of this article
    by Dimitrios Thomalos, Hossein Hassani 
    Abstract: The problem of optimal linear filtering, smoothing and trend extraction for m-period differences of processes with a unit root is studied. Such processes arise naturally in economics and finance, in the form of rates of change (price inflation, economic growth, financial returns) and finding an appropriate smoother is thus of immediate practical interest. The filter and resulting smoother are based on the methodology of Singular Spectrum Analysis (SSA). An explicit representation for the asymptotic decomposition of the covariance matrix is obtained. The structure of the impulse and frequency response functions indicates that the optimal filter has a permanent" and a transitory component", with the corresponding smoother being the sum of two such components. Moreover, a particular form for the extrapolation coefficients that can be used in out-of-sample prediction is proposed. In addition, an explicit representation for the filtering weights in the context of SSA for an arbitrary covariance matrix is derived. This result allows one to examine the specific effects of smoothing in any situation. The theoretical results are illustrated using different data sets, namely U.S. inflation and real GDP growth.
    Keywords: Core inflation; Business cycles; Differences; Euro; Linear filtering; Trend extraction and prediction; Unit root.

  • Bias decomposition in the Value at Risk calculation by a GARCH(1,1)   Order a copy of this article
    by Gholam Reza K. Haddad 
    Abstract: The recent researches show that Value at Risk estimations are biased and is calculated conservatively. Bao and Ullah (2004) proved the bias of an ARCH(1) model for VaR can be decomposed in to two parts: bias due to return misspecification distributional assumption for GARCH(1,1) (Bias1) and bias due to estimation error (Bias2). Using quasi maximum likelihood estimation method this paper intends to find an analytical framework for the two source of biases. We generate returns from Normal and t-student distributions, then estimate the GARCH(1,1) under Normal and t-student assumptions. Our findings reveal that Bias1 equals to zero for the Normal likelihood function, but Bias2 0. Also, Bias1 and Bias2 are not zero for the t-student likelihood function as analytically were expected. However all the biases become modest, when the number of observations and degree of freedom is large.
    Keywords: Value-at-Risk; GARCH(1,1); Second-order bias.

  • Performance Evaluation of the Bayesian and classical Value at Risk models with circuit breakers set up   Order a copy of this article
    by Gholam Reza K. Haddad 
    Abstract: Circuit breakers, like price limits and trading suspensions, are used to reduce price volatility in security markets. When returns hit price limits or missed, observed returns deviate from equilibrium returns. This creates a challenge for predicting stock returns and modeling Value at Risk (VaR). In Tehran Stock Exchange (TSE), the circuit breakers are applied to control for the excess price volatilities. We extend Weis (2002) model, in the framework of Bayesian Censored and Missing-GARCH approach, to estimate VaR for Iran Khodro Company (IKCO) share in TSE. Using daily data for the period of June 2006 to June 2016, we show that the Censored and missing- GARCH model with t-student distribution outperforms. Kullback-Leibler (KLIC), Kupic (1995) test and Lopez score (1998) outcomes show that estimated VaR by Censored and missing- GARCH model with t-student distribution is of the most accuracy among all other classical and Bayesian estimation models.
    Keywords: Circuit Breakers; Censored and Missing–GARCH; Bayesian estimation; Value at Risk; Ranking Models.

  • Stages and determinants of European Union Small and Medium Sized firms failure process   Order a copy of this article
    by Alexios Makropoulos, Charlie Weir, Xin Zhang 
    Abstract: This paper uses a combination of Factor and Cluster analysis to identify and compare failure processes in Small and Medium sized firms from a number of European Union countries. Panel data analysis is then used to identify the determinants of the firms transition from financial health towards liquidation in the alternative failure processes. The results suggest that there are 4 different firm failure processes. We find that financial performance and director characteristics differ between firm failure processes. We also find that the economic environment, the legal tradition of countries and excessive firm growth are determinants of the transition of firms towards liquidation across most firm failure processes. These findings may be of practical use to policy makers, lenders and risk managers who will benefit from a better understanding of the differences between the alternative firm failure processes and from the determinants of a firms transition towards liquidation within these failure processes.
    Keywords: SME failure; firm failure; firm failure process; factor/cluster analysis; ordered random effects regression; failure status transition.

  • Abnormal returns and systemic risk: evidence from a non-parametric bootstrap framework during the European sovereign debt crisis.   Order a copy of this article
    by Konstantinos Gkillas, Christos Floros, Christoforos Konstantatos, Dimitrios I. Vortelinos 
    Abstract: We investigate the impact of European Central Bank (ECB) interventions on major European and Turkish stock and credit default swap (CDS) markets highlighting the importance of abnormal to excess abnormal returns in the systemic risk. In particular, we examine the impact of ECB announcements (news) on major European and Turkish financial markets (stocks and CDSs indices) for a high and low-volatility period, i.e. from November 6th, 2008 to December 31st, 2015. We also examine the market efficiency by using both an event study methodology and the Capital Asset Pricing Model. Moreover, the impact of the ECB events is measured by an event study and a systemic risk analysis. The results show that investors exposed to Finland, Sweden, Austria and Spain tend to be more vulnerable to risk and volatility, when ECB announcements are published.
    Keywords: abnormal returns; bootstrap; ECB events; financial crises;.

  • An analysis of major Moroccan domestic sectors interdependencies and volatility spillovers using Multivariate GARCH models.   Order a copy of this article
    by Ouael EL JEBARI, Abdelati HAKMAOUI 
    Abstract: This paper tries to give a thorough analysis of the mechanisms of volatility spillovers, as well as, a study of the time-varying interdependencies of volatilities of seven major sectors of the Moroccan stock exchange by proposing an empirical approach based on multivariate GARCH models. It uses daily data spanning the period between 02/07/2007 and 15/12/2016, covering seven principal sectors indices. The results of the study confirm the existence of multiple volatility transmissions in both ways and of both signs between sectors of our sample, along with, the quasi-abundance of positive correlations suggesting possible contagion effects. More importantly, our findings are in line with those discovered in the U.S financial market. The notoriety of this article resides in the fact that it broadens previously documented studies focusing mainly on external shocks by providing a study of internal shocks while applying two multivariate GARCH models.
    Keywords: Volatility spillover; dynamic conditional correlations; interdependencies; domestic sectors; multivariate GARCH models.

  • A note on the use of the Box-Cox Transformation for Financial Data   Order a copy of this article
    by Dimitrios Kartsonakis Mademlis, Nikolaos Dritsakis 
    Abstract: This paper tests whether the Box-Cox transformation reduces the problem of non-normality in financial data.
    Keywords: ARIMA models; Box-Cox transformation; Box-Jenkins methodology; normality; stock market; oil prices.

Special Issue on: ICOAE2015 Applied Economics

  • Reconsidering the relationship between foreign direct investment and growth   Order a copy of this article
    by Carlos Encinas-Ferrer, Eddie Villegas-Zermeño 
    Abstract: It has been assumed that foreign direct investment (FDI) is a variable that explains economic growth (EG). As investment (I) is the dynamic element of gross domestic product (GDP), therefore, FDI, as part of total investment, should be also the independent variable and GDP growth the dependent one. However, many studies in many countries have shown the contrary, there is not such a causal relationship between FDI and GDP. In our investigation, we include the study of the cases of Mexico, China, Brazil and the Republic of Korea. It is our hypothesis that there is not a causal relationship between FDI, as the independent variable, and GDP grow as the dependent one in the selected countries and that this is in part because FDI is a small proportion of total (national and foreign) direct investment and so its impact is reduced.
    Keywords: FDI; foreign direct investment; GDP; gross domestic product; economic growth; gross fixed capital formation.
    DOI: 10.1504/IJCEE.2019.10011558

Special Issue on: ICOAE2016 Applied Economics

  • Causality among CO2 Emissions, Energy Consumption and Economic Growth in Italy.   Order a copy of this article
    by Pavlos Stamatiou, Nikolaos Dritsakis 
    Abstract: The aim of this paper is to investigate the relationship between CO2 emissions (carbon dioxide emissions), energy consumption and economic growth in Italy, using annual data covering the period 1960-2011. The unit root tests results indicated that the variables are not stationary in levels but in their first differences. Subsequently, the Johansen cointegration test showed that there is a cointegrated vector between the examined variables. The Vector Error Correction Model (VECM) is used in order to find the causality relations among the variables. The empirical results of the study revealed that both in the short and long run there is a strong unidirectional causality relation between economic growth and CO2 emissions with direction from economic growth to CO2 emissions. Finally, the impulse response functions indicated that a reduction in CO2 emissions has a positive effect on energy consumption, while it causes a decrease in economic growth.
    Keywords: Carbon emissions; Energy consumption; Economic Growth; Cointegration Test; Vector Error Correction; Causality; Variance Decomposition; Impulse response analysis; Italy.

  • The Public Sector Wage Premium Puzzle   Order a copy of this article
    by Yi Wang, Peng Zhou 
    Abstract: This paper investigates the public sector wage premium in the UK over the first decade of the 21st century using both econometric and economic modelling methods. A comprehensive literature review is conducted to summarise the four popular types of methods adopted by the traditional microeconometric studies. Application of these methods results in an estimated public sector wage premium equal to 6.5%. Indirect inference is then introduced as a new method of testing and estimating a microfounded economic model. All four types of econometric methods can be used as auxiliary models to summarise the data features, based on which the distance between the actual data and the model-simulated data is assessed. The selection bias can also be tested in a straightforward way under indirect inference.
    Keywords: Public Sector Wage Premium; Microfoundation; Propensity Score Matching; Indirect Inference.

  • Modelling Agricultural Risk in a Large Scale Positive Mathematical Programming Model   Order a copy of this article
    by Ivan Arribas, Kamel Louhichi, Angel Perni, Jose Vila, Sergio Gomez-y-Paloma 
    Abstract: Mathematical programming has been extensively used to account for risk in farmers' decision making. The recent development of the Positive Mathematical Programming (PMP) has renewed the need to incorporate risk in a more robust and flexible way. Most of the existing PMP-risk models have been tested at farm-type level and for a very limited sample of farms. This paper presents and tests a novel methodology for modelling risk at individual farm level in a large scale model, called IFM-CAP (Individual Farm Model for Common Agricultural Policy analysis). Results show a clear trade-off between including and excluding the risk specification. Albeit both alternatives provide very close estimates, simulation results shows that the explicit inclusion of risk in the model allows isolating risk effects on farmer behaviour. However, this specification increases three times the computation time required for estimation.
    Keywords: agriculture; positive mathematical programming; risk and uncertainty; expected utility; Highest Posterior Density; European Common Agricultural Policy.

  • Overvaluation in a non-optimal currency area   Order a copy of this article
    by Carlos Encinas-Ferrer 
    Abstract: The devaluation tool in an optimal currency area with monetary sovereignty has a significant importance in determining economic policies to adjust relative costs and interest rates to the situation faced by a country in front of economic shocks, either asymmetric or generalized. Devaluation risk is due not only to domestic inflation but to its relationship with that of its major trading partners. If inflation of a nation is greater than the average one of its trading partners and the gap between them is not adjusted by the depreciation of its currency, it will start a process of overvaluation. This overvaluation ends manifesting itself by a growing lack of competitiveness in its foreign trade showed by trade deficit, reduced gross domestic product (GDP) and rising unemployment. Devaluation or depreciation would restore the competitiveness of the productive apparatus. However, in a non-optimal currency area -as a country unilaterally dollarized- this adjustment may be made by abandoning the anchor coin and adopting a new national currency, what it has been called remonetization (Encinas-Ferrer 2003-1 and 2) but the Eurozone experience from 2011 shows us that abandoning a non- optimal currency area and stablishing a new national currency is a very difficult decision that no one has dared to take until now.
    Keywords: overvaluation; optimal currency areas; non-optimal currency areas; euro-zone.

  • Evidence for the Globalization Types Model Integrating Different Trade Theories   Order a copy of this article
    by Bruno G. Rüttimann 
    Abstract: This paper summarizes the research work performed during the last ten years regarding the globalization phenomenon measuring and analyzing the evolution of trade globalization of the period 2003-2015. The goal was to find evidence for a new Globalization Types Model. Indeed, the economic system has become more complex during recent years, the current trade models not being able to capture individually all the different aspects as well as not being universally applicable. The evolution of globalization has been measured with a new entropy-based metric that computes the interweavement of trade flows. The research has shown that economic world trade, as a whole, has been globalizing during recent years but with different patterns: de-globalizing for advanced economic regions and globalizing for emerging economic regions. These differences can be explained with the Globalization Types Model by integrating neoclassic trade theories. Furthermore, the aggregated result seems to confirm inverse Kuznets evolution of globalization. The analysis has been leading to enounce seven Trade Globalization Postulates explaining the phenomenon of trade globalization evolution.
    Keywords: Globalization types; globalization forms; globalization models; inequality metric; trade flows; foreign trade; trade theory; Kuznets.

  • Depth, tightness, and resiliency as market liquidity dimensions: evidence from the Polish stock market   Order a copy of this article
    by Joanna Olbrys, Michal Mursztyn 
    Abstract: Liquidity in a financial market is not a one-dimensional variable but it includes several dimensions. The main aim of the paper is an empirical analysis of market liquidity dimensions on the Warsaw Stock Exchange (WSE). We investigate market depth, market tightness, and market resiliency for fifty-three WSE-listed companies divided into three size groups. The high-frequency data covers the period from January 3, 2005 to June 30, 2015. The additional goal is a robustness analysis of the obtained results with respect to the whole sample period and three adjacent subsamples, each of equal size: pre-crisis, crisis, and post-crisis periods. Order ratio (OR) is employed as a proxy of market depth. Market tightness is approximated by using relative spread (RS). Market resiliency is estimated by utilizing realized spread (RealS) which is a temporary component of bid/ask effective spread. As we expected, the empirical results indicate that OR values do not depend on a firm size, while RS estimations are slightly higher for small companies. RealS proxy values are positive for almost all stocks, except for isolated cases. Moreover, the results turn out to be robust to the choice of the sample for all groups of assets.
    Keywords: dimensions of market liquidity; market depth; market tightness; market resiliency; Global Financial Crisis; Polish stock market.

Special Issue on: ICOAE2017 Applied Economics

  • An Analysis of Long-Run Relationship between ICT Sectors and Economic Growth: Evidence from ASEAN Countries   Order a copy of this article
    by Chukiat Chaiboonsri, Satawat Wannapan 
    Abstract: This paper is proposed to investigate the causal panel relationship between information and communication technology (ICTs) segments and economic expansionary rates in ASEAN countries. Methodologically, the panel time-series data observed during 2006 to 2016 is employed to estimate the panel Granger Causality test. According to the technical problem of lag selection for the panel causal analysis, the computationally statistical approach called Newtons optimization method is helpfully applied to verify the suitable lag selection. The empirical results found that ICTs are not the major factor that causally motivates economic growth in ASEAN. This is confirmed by the extended section of the Autoregressive Distributed Lag (ARDL) cointegration approach, which is based on Bayesian statistics combining with the simulation method called Markov Chain Monte Carlo (MCMC). The results state Thailand is the only one among eight selected countries in ASEAN contained the long-run relationship between ICTs and GDP. This can be strongly concluded that the ICT sectors are not sustainable for driving economic growth in ASEAN. To address the issue, equitable educational systems and advanced infrastructural developments are the primary that should be corporately implemented.
    Keywords: ICT segments ;economic growth ;long-run relationship ;ASEAN countries;Bayesian approach.

Special Issue on: MIC 2017 Managing the Global Economy

  • Stabilization Policies in a Small Euro Area Economy: Taxes or Expenditures? A Case Study for Slovenia   Order a copy of this article
    by Klaus Weyerstrass, Reinhard Neck, Dmitri Blueschke, Boris Majcen, Andrej Srakar, Miroslav Verbič 
    Abstract: In this paper we investigate how effective stabilization policies can be in a small open economy which is part of the Euro Area, namely Slovenia. In particular, we analyse whether tax policy or expenditure policy has stronger multiplier effects. Slovenia is an interesting case because it is a small open economy in Central Europe that was already in the Euro Area before the Great Recession. Using the SLOPOL10 model, an econometric model of the Slovenian economy, we analyse the effectiveness of some categories of taxes and public spending. Some of these instruments are targeted towards the demand side, while others primarily influence the supply side. Our results show that those public spending measures that entail both demand and supply side effects are more effective at stimulating real GDP than pure demand side measures. Measures that improve the education level of the labour force are very effective at stimulating potential GDP. Employment can be most effectively stimulated by cutting the income tax rate and the social security contribution rate, i.e. by reducing the tax wedge on labour income, thereby positively affecting Slovenias international competitiveness. On the other hand, simulations show that fiscal policy measures can only mitigate but not undo the adverse effects of a crisis like the Great Recession.
    Keywords: Macroeconomics; stabilization policy; fiscal policy; tax policy; public expenditures; Slovenia; public debt; econometric model; simulation.

Special Issue on: Coping with Uncertainty in Complex Socio-Economic Systems

  • Career mobility of PhD holders in Social Sciences and Humanities: evidences from the POCARIM project   Order a copy of this article
    by Lucio Morettini, Emilia Primeri, Emanuela Reale, Antonio Zinilli 
    Abstract: The paper aims at investigating factors that could affect the likelihood of changing job of PhD holders in the fields of social sciences and humanities (SSH). We use data collected through a survey developed within the POCARIM project (funded by the EC under the EUFP7) in order to analyse variations in PhDs\' career paths in a longitudinal dimension: we consider the career of each agent as a whole and investigate what elements related to individual features can influence careers entropy in term of changes of sector and/or country.
    Keywords: Career mobility; PhD; Job market; Higher education; Career paths.

  • Technology Diffusion of Industry 4.0: An Agent-Based Approach   Order a copy of this article
    by Martin Prause, Christina Gunther 
    Abstract: Governmental interventions, such as public policies and programs, play a vital role in innovation diffusion, particularly if the application area is heterogeneous, like the German federal high-tech approach of Industry 4.0. Interventions can thus inhibit market failure and negative externalities or disseminate the technology and promote positive externalities. To analyze the impact of governmental intervention, considering the particularities of the Industry 4.0 approach, an agent-based model is proposed, particularly to test the sensitivity of Industry 4.0 innovation diffusion speed and degree due to interventions such as promotion, educational support, technology networks (hubs), technology standardization, and financial aid among manufacturing SMEs in Germany. This article describes a conceptual model structured along the overview, design concept, and details framework. Grounding and calibration of input parameters and agent behavior are based on firm characteristics and adoption determinants (technology-organization-environment model) from survey data and Industry 4.0 case studies.
    Keywords: Agent-based Model; Industry 4.0; Innovation Diffusion; SME; Technology Adoption.

  • Forecasting Inflation in Tunisia during Instability: Using Dynamic Factors Model A two-step based procedure based on Kalman Fitler   Order a copy of this article
    Abstract: This work presents a forecasting inflation model using a monthly database. Conventional models that forecast inflation use a few macroeconomic variables. In the context of globalization and dependent economic world, models have to take into account a large amount of information. This model is the goal of recent research in various industrialized countries as well as developing ones. With the Dynamic Factors Model (DFM), the forecast values are closer to the actual inflation than those obtained from the conventional models in the short term. In our research, we devise the inflation into free and administered inflation and test the performance of the DFM under instability (before and after the revolution) in different types of inflation and trend inflation, namely administered and free inflation. Knowing that periods of instability are simultaneously the period of price liberalization of basic goods (2008) and the post-revolution period (2011-2017). We have found that the DFM with an instability factor leads to substantial forecasting improvements over the DFM without an instability factor in the period after the revolution.
    Keywords: Inflation forecasting; PCA; VAR; Dynamic Factors Model; Kalman Filter; Space-state; Instability factor.

  • Do the Flexible Employment Arrangements Increase Job Satisfaction and Employee Loyalty? Evidence from Bayesian Networks and Instrumental Variables   Order a copy of this article
    by Eleftherios Giovanis 
    Abstract: This study explores the relationship between job satisfaction, employee loyalty and two types of flexible employment arrangements; teleworking and flexible timing. The analysis relies on data derived by the Workplace Employee Relations Survey (WERS) in 2004 and 2011. We apply the propensity score matching approach and least squares regressions. Furthermore, we employ the Bayesian Networks (BN) and Directed Acyclic Graphs (DAGs) to confirm the causality between employment types explored and the outcomes of interest. Additionally, we propose an instrumental variables (IV) approach based on the BN framework. The results support that a positive causal effect from these employment arrangements on job satisfaction and employee loyalty is present.
    Keywords: Bayesian Networks; Directed Acyclic Graphs; Employee Loyalty; Employment Arrangements; Flexible Timing; Job Satisfaction; Teleworking; Workplace Employment Relations Survey.

  • On the Validity of Exclusion Restrictions in the Structural Multivariate Framework: a Monte Carlo Simulation   Order a copy of this article
    by Talel Boufateh 
    Abstract: This paper aims to examine the validity of identifying restrictions used in the Structural multivariate models. Whether we are under short-term identification approach and / or long term identification one, the scheme adopted implies the imposition of additional assumptions which usually take the form as exclusion restrictions. We believe however, that the value of a restriction is not necessarily equal to zero even if it expresses the lack of impact of a shock on a variable. We think that this lack of impact may reflect an effect asymptotically equal to zero and that the little nuance could be amplified with the model dynamics and affect the structural analysis. We have chosen to study this problem by using a Monte Carlo simulation and to examine the consequences of slipping of the identification restriction value. The results that emerge from this work confirm the sensitivity of variables' responses to change, even the slightest it may be, in the value of identification restrictions. Whatever the strength and elegance of the theory and the economic reasoning from which emanate the exclusion restrictions, precision measurements should be considered.
    Keywords: Exclusion restrictions; SVAR approach; Monte Carlo Simulation.

  • Measuring Uncertainties: a Theoretical Approach   Order a copy of this article
    by Carolina Facioni, Isabella Corazziari, Filomena Maggino 
    Abstract: When our aim is to draw the possible developments of future events, we are faced with a practical obstacle. Indeed, we cannot have any empirical experience of the future. Have we, therefore, to be inferred that forecasting, exploring future or, better: exploring futures, or anticipating futures have not to be considered activities of a scientific kind? Answer to such a difficult question requires a multidisciplinary approach, where statistical models, methodology of social science and of course statistics and sociology as a whole are enhanced in their ability to express the change and sometimes the risk that the change itself implies. A great help in understanding complexity, and trends, comes from a method for multi-way data, based on the joint application of a factorial analysis and regression over time, called dynamic factor analysis (DFA)
    Keywords: uncertainty measure; futures studies; DFA; dynamic factor analysis.
    DOI: 10.1504/IJCEE.2018.10011864