International Journal of Computational Economics and Econometrics (23 papers in press)
ENSEMBLE MARGIN BASED RESAMPLING APPROACH FOR A COST SENSITIVE CREDIT SCORING PROBLEM
by Meryem Saidi, Nesma Settouti, Mostafa El Habib Daho, Mohammed El Amine Bechar
Abstract: In the past few years, a growing demand for credit compel banking
institution to contemplate machine learning techniques as an answer to obtain
decisions in a reduced time. Different decision support systems were used to
detect loans defaulters from good loans. Despite good results obtained by these
systems, they still face some problems such as imbalanced class and imbalanced
misclassification cost problems. In this work, we propose a cost sensitive credit
scoring system, based on a two-step process. The first is a resampling step which
handles the imbalance data problem followed by a cost sensitive classification
step that recognizes potential insolvent loans red in order to reduce financial
loss. A resampling algorithm called Ensemble Margin for Imbalanced Instance
(EM2I) is suggested to manage imbalanced datasets in cost sensitive learning.
We compare our algorithm with other techniques from the state of the art and
experimental results on German credit dataset demonstrate that EM2I leads to a
significant reduction of the misclassification cost."
Keywords: Cost sensitive learning; imbalanced problem; ensemble margin; credit scoring.
A nonparametric estimator for stochastic volatility density
by Soufiane Ouamaliche, Awatef Sayah
Abstract: This paper aims at improving the accuracy of stochastic volatility density estimation in a high frequency setting using a simple procedure involving a combination of kernel smoothing methods namely, kernel regression and kernel density estimation. The employed data, which are thirty years worth of hourly observations, are simulated through a Constant Elasticity of Variance-Stochastic Volatility (CEV-SV) model, namely the Heston Model, calibrated to fit the S&P500 index, in the form of a two-dimensional diffusion process (Yt,Vt) such that only (Yt) is an observable coordinate. Polynomials of different degrees are then adjusted using weighted least squares to filter the observations of the variance coordinate (Vt) from a convolution structure before applying a straightforward kernel density estimation. The obtained estimates did well when compared to previous results as they have displayed a certain improvement, linked to the degree of the fitted polynomial, by reducing the value of the Mean Integrated Squared Error (MISE) criterion computed with respect to a benchmark density suggested in the literature.
Keywords: nonparametric estimation; kernel smoothing; kernel regression; kernel density estimation; convolution structure; stochastic volatility; Monte Carlo simulations.
Simulating Long Run Structural Change with a Dynamic General Equilibrium Model
by Roberto Roson, Wolfgang Britz
Abstract: There is an increasing demand for the construction of long-term economic scenarios, possibly with a sectoral detail comparable with the one provided by input-output or social accounting matrices. This paper illustrates how an especially designed, recursive dynamic CGE model can be used to this purpose. The general equilibrium model (G-RDEM) features a non-homothetic demand system, endogenous saving rates, differentiated industrial productivity growth, interest payments on foreign debt and time-varying input-output coefficients. When the model is forced to follow given projections of GDP and population, it produces a wealth of detailed, consistent data on macroeconomic variables such as: consumption patterns, industrial production volumes, resources use and trade flows. We present in this paper the results of a baseline construction exercise, which allow us to identify which structural adjustment processes will likely be most relevant in shaping the future structure of the global economy. Our numerical tests suggest that one very important factor is the decline in the aggregate saving rates (due to higher dependency ratios in the demographic structure), which influences capital stock accumulation, investments, composition of the final demand and productivity. In terms of employment of primary resources, we detected a general pattern of decline in the primary sector, compensated by an increase in several service industries. We also found that some forces shape the global outcomes, some others produce implications which are relevant at the regional or industrial scale.
Keywords: Computable General Equilibrium models; Long-run economic scenarios; Structural change; Economic growth.
Testing for Panel Cointegration in High Dimensional Data in the Presence of Cross-Sectional Dependency
by RASHID MANSOOR, Kristofer Månsson, Pär Sjölander
Abstract: This paper introduce some new methods to test for panel cointegration in the error correction framework. These methods are proposed since the previous approaches does not perform well when the number of cross-sectional units (N) are approximately equal to the number of time periods (T). By means of Monte Carlo simulations we investigate the size and power properties when N and T increase simultaneously i.e. N/T-> c; where 0 Keywords: Error correction model; Panel cointegration; Increasing dimension.
Causal statistics of structural dependence space-based trend simulations for the coalition of rice exporters: the cases of India, Thailand, and Vietnam
by Anuphak Saosaovaphak, Chukiat Chaiboonsri, Satawat Wannapan
Abstract: This paper is a contribution seeking an econometric solution for the mathematical problem known as a cooperative game. The theoretical coalition of world major rice exporters includes India, Thailand, and Vietnam. In terms of methodological processes, yearly time-series variables (2008-2018) such as the values of rice production, rice consumption, and rice exporting profits are observed. The causal model is employed to clarify three mixed approaches. The first is the structural dependent analysis based on Bayesian statistics referred to as the Bayesian Copula. The empirical results confirm that these three countries have deep structural dependences in the market. In the second method, the trends of observed variables are predicted by the Bayesian structural time-series model. The last section is the Shapley value with coalition scenarios. Optimized results causally prove that rice exporting profits are a double increment when cooperative behaviors continuously exist. Hence, the potential outcomes framework is to finally recognize the Organization of Rice Exporting Countries (OREC).
Keywords: Rice exports; Bayesian copulas; Bayesian structural time-series analysis; Shapley value; Coalition game.
Analyzing the degree of integration of the euro area: How a lack of complete markets and insufficient risk sharing raise concerns about its durability and stability
by Januj Juneja
Abstract: The goal of the creation of the euro area (EA) was to bring forth a common currency and interest rate structure that would reduce risk associated with trade across its members that, over time, would lead to a convergence in the prices of financial markets containing important economic variables and an increase in integration. However, as we demonstrate in the current study through the development of formal hypotheses that exploit the link between integration, the completeness of financial markets, and risk sharing, in the current state of the EA, there is a large amount of variation in the degree of integration and risk sharing across EA member states. Even if the EA experienced full integration, its financial markets were complete, and it experienced complete risk sharing, to the extent that these are theoretically feasible, our finding remains intact. Some states reap inconsequential gains in the extent of their integration and ability to share risks within the EA, while its variation in integration and risk sharing remains quite large across member states, raising concerns about the EAs durability and stability. We assess the validity of our hypotheses by measuring integration through the estimation of dynamic term structure models that price both currency and interest rate risk in EA member states. Finally, we recognize that our results may owe to myriad sources of uncertainty in the EA. Thus, we also design, construct, and implement using NSF granted supercomputing resources, several Monte Carlo simulation experiments to conduct scenario analyses to incorporate broader sources of uncertainty into our study.
Keywords: Integration; Euro area; Risk sharing; Market completeness; Uncertainty modeling.
The Effects of Education and Experience on Youth Employee Wages: The Case of Turkey
by Ebru Caglayan Akay, Fulden Komuryakan
Abstract: The aim of this study is to reduce the disadvantages experienced by young Turkish employees, such as age discrimination, by analysing their wage structure and the factors that could affect their earnings. This study could fill the gaps in the literature on youth employee wages in the Turkish labour force. Using the 2018 Household Budget Survey data, this study addresses five research questions, estimates the extended Mincer wage equation with robust estimators to respond to the research questions. The findings show that postgraduate and bachelors degrees have a high incremental effect on wages and the wage gaps between the degrees are wide. Each added year of experience impacts wages because employers prefer more experienced employees to avoid the cost of training them. Young female employees earn less than young male employees because of occupational segregation, motherhood penalty, and gender norms. Due to the lack of opportunities for part-time jobs in the Turkish labour force, there is a wide gap between the wages for full-time and part-time jobs. This study contributes to a better understanding of young employees' wage structure with robust-to-outliers econometric analysis and may guide to develop techniques to reduce the disadvantages for young Turkish individuals in the labour market.
Keywords: Mincer; youth labour market; wage equation; robust regression; S; MM; Turkey.
Investigating the Monetary and Fiscal Policy Regimes Dominance for Inflation Determination in Nigeria: A Bayesian TVP-VAR Analysis
by Olusola Oyeleke, Lukman Oyelami, Adeyemi Ogundipe
Abstract: Persistent increase in general price level has been generating policy issues between monetary and fiscal authorities in Nigeria. This study explores dominance of policy regime (monetary versus fiscal) and extends the analysis to inflation determination in Nigeria from 1981 to 2016. The study makes use of secondary data sourced from Central Bank of Nigeria (CBN) Statistical Bulletin, 2016. Stationarity properties of the variables are examined using Augmented Dicky-Fuller (ADF) and Philip-Perron (PP) unit root tests. Johansen cointegration test results show the presence of long run relationship among the variables. The study employs Bayesian Time Varying Parameter Vector Auto Regression (TVP VAR) with stochastic volatility and draws sample with Markov Chain Monte Carlo (MCMC) to generate impulse response functions. The results show that there is no definite policy regime dominating in the economy of Nigeria. The implication is that inflation problem could not be attributed to a particular policy regime. Therefore, for ease of adjustments, a definite policy regime should be allowed to prevail to achieve price stability in the economy of Nigeria.
Keywords: Bayesian TVP-VAR; fiscal policy; monetary policy; Nigeria; inflation.
The Effect of Female Employment on Saving-Investment Gap and the Role of Their Interaction in the Economic Growth
by Oznur Ozdamar, Sibel Gunduz, Eleftherios Giovanis
Abstract: A large number of countries experience negative saving-investment (S-I) gaps, which can be detrimental to economic growth. Earlier literature indicates that women save more than their male counterparts. In this study, our preliminary aim is to understand, whether female employment rates increase domestic savings that could potentially contribute positively to the S-I gaps in the low and middle-income countries. Second, we aim to investigate whether the interaction of female employment rates and S-I gap matters for economic growth. The entire analysis relies on panel data from 74 low and middle-income countries over the period 2000-2017. Various panel data techniques are applied, and they reveal similar results. The main finding of the study shows that low levels of female employment rate, and therefore inferior female earnings, are obstacles to an adequate amount of savings accumulation, necessary to close the savings-investment gap and thus, to enhance economic growth.
Keywords: Economic Growth; Female Employment Rate; Gender-Wage Gap; Low and Middle Income Countries; Panel Data Analysis; Saving-Investment Gap.
Tax Benefits Determinants and Earnings Management: Results from the Eurozone Countries
by Panagiotis Tachinakis
Abstract: Previous evidence indicates that there are considerable benefits for firms operating in tax havens, defined as countries that provide tax benefits to attract foreign capital. Using a sample of Eurozone countries along with tax haven country rankings, we examine how firms adjust their level of earnings management in response to some countries tax benefits. We also explore whether and to what extent countries different tax characteristics influence the relationship between earnings management and the existence of tax benefits. Our findings indicate that firms domiciled in countries with lower tax rates have lower levels of earnings management than companies domiciled in other European countries. However, countries with higher tax contribution rates and higher tax haven scores have lower earnings management scores. Our results suggest that firms domiciled in tax havens have interests other than just the low tax rates. In fact, the more flexible regulatory environment in these countries is a key feature that attracts firms to tax havens.
Keywords: Earnings management; tax havens; tax revenue.
A SAS Macro for Examining Stationarity Under the Presence of up to m Endogenous Structural Breaks with an Application on EU28 Agri-Food Exports
by Dimitrios Dadakas
Abstract: I present a SAS macro, that allows the examination of stationarity under the presence of up to $m$, endogenously determined, structural breaks using the methodology presented by Kapetanios (2005). The computationally intensive grid-search procedure allows researchers with minimum programming skills to easily apply the macro to the scope of their research. I demonstrate the macro using EU28 exports of agro-food products, HS categories 1 through 24. The code prepares a report of the results in PDF format.
Keywords: Endogenous Structural Breaks; Stationarity; Time Series; SAS; Macro.
A comparison of SVR and NARX in financial time series forecasting
by Engin Tas, Ayca Hatice Atli
Abstract: Machine learning techniques have become attractive due to their robustness and superiority in predicting future behavior in various areas. This paper is aimed to predict future stock prices by applying a non-linear autoregressive network with exogenous inputs (NARX) and support vector regression (SVR). For this aim, we use the daily trade data, including highest price, lowest price, closing price, and trade volume for the stocks with the highest transaction volumes from Borsa Istanbul (BIST). In order to evaluate the performance of the prediction models, various statistical measures are used. The experimental results indicate that the techniques used are quite capable of predicting the future price of a stock. Moreover, both methods are competitive with each other and have superiorities in different aspects.
Keywords: artificial learning; artificial neural networks; financial time series forecasting; nonlinear autoregressive network with exogenous inputs; support vector regression.
Bootstrapping the log-periodogram estimator of the long-memory parameter: is it worth weighting?
by Saeed M. Heravi, Kerry D. Patterson
Abstract: Estimation of the long-memory parameter from the log-periodogram (LP) regression, due to Geweke and Porter-Hudak (GPH), is a simple and frequently used method of semi-parametric estimation. However, the simple LP estimator suffers from a finite sample bias that increases with the dependency in the short-run component of the spectral density. More recently, Arteche and Orbe (2009a, 2009b), in the context of the GPH estimator, suggested a promising bootstrap method, based on the frequency domain, to obtain the RMSE value of the frequency bandwidth, m, that avoids estimating the unknown parameter. We extend this bootstrap method to the AG and WLP estimators and to consideration of bootstrapping in the frequency domain (FD) and the time domain (TD) and, in each case, to 'blind' and 'local' versions. We undertake a comparative simulation analysis of these methods for relative performance on the dimensions of bias, RMSE, confidence interval width and fidelity.
Keywords: long memory; bootstrap; log-periodogram regression; variance inflation; weighted log-periodogram regression; time domain; frequency domain.
R&D cooperation performance inside innovation clusters
by B.G. Jean Jacques Iritié
Abstract: This paper theoretically analyses the effects of innovation cluster on R&D cooperation outcome in terms of private R&D investments. We develop a two-stage strategic R&D game with a duopoly in an innovation cluster. The two firms first conduct cooperatively their R&D decisions in a research joint venture (RJV) before competing in Cournot fashion on the market product. The results show that an innovation cluster improves private R&D investments and social welfare through informational incentives. Then, belonging to an innovation cluster strengthens the willingness to cooperate in R&D and partnership. However, the model also show that innovation clusters can lead to a risk of monopolisation of the market that could be extended even beyond cooperation; this risk thus makes it possible to relativise the expected positive effects of innovation cluster policy on R&D cooperation.
Keywords: innovation cluster; research joint venture; RJV; localised knowledge spillovers; LKS; informational incentives; R&D cooperation performance.
The impact of the CAP Health Check on the price relations of the EU food supply chain: a dynamic panel data cointegration analysis
by Anthony N. Rezitis, Andreas Rokopanos
Abstract: The CAP Health Check at the end of 2008 attested to the liberalisation initiated in the 2003 CAP Reform concerning the policy measures intended to protect farmers across Europe. It was agreed that several restrictions, including the remaining coupled payments, the set-aside requirements and the milk quotas, would be removed. This study investigates the price relations along the EU food supply chain based on a panel cointegration and error correction vector autoregressive approach. Our panel data comprise monthly observations from January 2005 to September 2012 in 19 European countries. The sample is split into two sub-periods, January 2005 to December 2008 and January 2009 to September 2012, to examine how the CAP Health Check has affected price relations. The empirical results indicate that the decreased support in the agricultural sector after the CAP Health Check has rendered agricultural prices more respondent to market signals, suggesting a more liberalised market.
Keywords: panel cointegration; error correction vector autoregressive; EC-VAR model; causality analysis.
Two algorithms in sign restrictions: an exploration in an empirical SVAR
by Lance A. Fisher, Hyeon-seung Huh
Abstract: This paper investigates whether the key choices for the implementation of algorithms in sign restrictions are consequential for the range of accepted impulse responses in an empirical SVAR. Two algorithms in sign restrictions are considered. In one algorithm, the key choices concern the method by which an initial set of orthogonal shocks are formed and the method by which they are rotated. For this algorithm, the range of accepted responses are invariant to these choices. In the other algorithm, the key choice is the selection of the set of coefficients on the contemporaneous variables in the structural equations which are to be generated. Each selection corresponds to an ordering of the variables. For this algorithm, the range of accepted responses can be affected by the ordering of the variables in which case the algorithm is extended to loop over all variable orderings.
Keywords: structural vector autoregressions; sign restrictions; Givens rotations; QR decomposition; instrumental variables; impulse responses.
Special Issue on: ICOAE2017 Applied Economics
Demand monotonicity of a pavement cost function used to determine Aumann-Shapley values in highway cost allocation
by Dong-Ju Lee, Saurav Kumar Dubey, Chang-Yong Lee, Alberto Garcia-Diaz
Abstract: Pavement thickness and traffic lanes are two essential requirements affecting the cost of a highway design project. The traffic loadings on a pavement are typically measured in 18-kip equivalent single axle loads (ESALs). In this paper, both ESALs and lanes are treated as two types of players and a pavement cost function is developed to determine the average marginal cost for each type of players. These averages are known as the Aumann-Shapley (A-S) values and are used to allocate the highway cost among all vehicle classes. The proposed pavement cost function is proved to be monotonically increasing as the traffic loadings (ESALs) are increased, a necessary condition for the function to be acceptable for computing Aumann-Shapley values. A severe limitation of the procedure to calculate marginal costs for the traffic-loading players is the extremely large number of permutations since the number of players is enormously high. To overcome this limitation, this article derives a compact form for the discrete A-S values of ESALs and lanes that allows the Aummann-Shapely values to be calculated in a computationally effective manner.
Keywords: cooperative game theory; highway cost allocation; HCA; linear optimisation; demand monotonicity; transportation economics; pavement cost estimation.
Special Issue on: Spatial Analysis and Interaction in Economics and Econometrics Data and Modelling for Sustainable Spatial Systems
A dose response evaluation of regional incentives to R&D
by Raffaele Spallone, Giovanni Cerulli
Abstract: The paper investigates the effects of regional research and development (R&D) incentives granted by the Italian regions in the period 1999-2016 on the performance of the different regional economies. We adopt a continuous treatment model that allows us to analyze the impact of the public support on a series of outcome variables. By studying the shape of the dose response function, i.e. the average treatment effects over all the possible values of the treatment levels, we are able to gauge the impact of public R&D on business performance when the level of the aid intensity changes. By this strategy, we are able to catch differences due a different policy exposure (or dose) provided at regional level. In fact, the dose-response approach employed in this study is suited when treatment is continuous, and individuals may react heterogeneously to observable confounders. The empirical analysis is carried out on a novel dataset built on purpose, which consists of a panel covering the whole amount of R&D incentives granted by the Italian regions to business activities between 1999 and 2016. We built our database using data sources made available by the Italian Ministry of Economic Development (MISE).
Keywords: State aid; evaluation of public policy; R&D incentives; cohesion.
Perspective of an exchange rate policy for global financial systems: evidence between China and ASEAN countries
by Chukiat Chaiboonsri, Satawat Wannapan, Nisit Phanthamit
Abstract: Currency rate fluctuations are essential drivers of international trade in mainland China and South East Asia, with the Chinese currency influencing deeply the economies of ASEAN countries. By employing copulas models, this paper investigates empirically currencies structural dependences. The relationships between RMB Chinese Yuan and ASEAN currencies are thus computationally analyzed. Our approach structurally classifies the flows and impulse responses activated by currency appreciation and depreciation. Additionally, agent-based simulations are carried out to depict systematical economic scenarios under currency fluctuation, thus providing suitable alerts for decision-makers when dangerous outlooks concerning trade dynamics in Indochina can take place.
Keywords: Exchange rates; Macroeconomics; Economic extreme cases; Copulas; Agent-based analysis; Monte Carlo simulation; China; ASEAN.
Transnational public research funding in Europe: exploring proximity dimensions in the ERA-NET programmes
by Antonio Zinilli, Andrea Orazio Spinello, Emanuela Reale
Abstract: This paper explores the factors that affect the decisions of policy makers at the national level for what concerns engaging in transnational joint research activities and mobilizing dedicated financial resources. The authors test whether different levels of proximity are likely to influence the emergence of similar patterns across countries in terms of participating in transnational research programmes. The research question is investigated by analyzing JoREP 2.0, a database containing data on the organisational and financial characteristics of transnational joint research programmes in Europe and the policy actors involved. Heterogeneity of socio-economic research objectives and closeness in domestic Research and Development funding and scientific performance are likely to influence the commitment of financial resources by European countries in joint research programmes, such as ERA-NETs.
Keywords: Public Research Funding; Proximity; Spatial Models; ERA-NET Programmes.
Simulating the effect of El Ni
by Edmondo Di Giuseppe, Gianfranco Giulioni, Massimiliano Pasqui
Abstract: This work analyzes the impact that the fluctuations of the large-scale atmospheric-oceanic phenomenon known as El Ni
Keywords: Computational model; Wheat international markets; Climate variability; Robust Anova regression; price cross-section distributions.
EXPLORING BREXIT IMPLICATIONS: THE IMPACT OF LONGER JOURNEY TIMES
by Bernard Fingleton
Abstract: Brexit implies longer journey times between UK and EU regions. In this paper the elasticity of trade with respect to journey time by goods vehicles is estimated, and the impact of this on employment is evaluated using a dynamic spatial panel data model. The estimator allows for the presence of endogenous and predetermined causal variables, regional interdependence, and attempts to control for common factors causing macro-economic variation over the estimation period. The estimates show that a job shortfall can be expected in both the UK and EU regions, with considerable diversity of outcome across regions.
Keywords: journey times; dynamic spatial panel model; regional employment.
Does spatial location affect business liquidations?
by Alexios Makropoulos, Charlie Weir, Xin Zhang
Abstract: Current studies in aggregate business liquidations have paid little attention to the potential importance of firms geographical (spatial) location. There is some evidence of spatial concentration of economic activity in certain geographical across Europe which crates firm interdependence. However, the literature does not currently provide evidence for the potential existence of spatial effects in business liquidations that could be influenced from business interdependence in certain geographical areas. This study investigates the potential existence of spatial effects in liquidated businesses in a sample of European countries. As such, it investigates the extent to which spatial econometrics can provide further insights into the study of aggregated business liquidations. Statistically significant spatial effects were detected in the form of SE and SD spatial models. These results confirm the existence of spatial effects in business liquidations, implying that the spatial location should be considered for modelling and policy making purposes. As such, further research is needed in this area so as to further explore the impact of the spatial aspect.
Keywords: Business failure; liquidations; Spatial effects; European countries.