International Journal of Computational Economics and Econometrics (7 papers in press)

Regular Issues

• A bibliometric survey of macroeconomic topics in agent-based models  
  by Emiliano Alvarez 
  Abstract: In recent decades, the analysis of economies and their different sectors has intensified through simulations based on agent-based models (ABM). This is especially relevant for macroeconomics, since these methodologies allow us to analyse macroeconomic phenomena from actions and the interaction between individuals. In this article, a bibliometric analysis of ABMs in macroeconomics is briefly shown from the information gathered in the databases of the Web of Science (WOS) and Scopus. The main results of this work show that ABMs have analysed a wide spectrum of the most relevant topics in macroeconomics. There is a greater emphasis on credit crisis and financial instability, explained by the possibilities of this type of implementation to simulate network effects. These works are concentrated in a few research centers, mainly in Europe. In recent years, the agenda of topics to be addressed has grown, as well as the possibilities of a multidisciplinary agenda.
  Keywords: agent-based model; ABM; economics; macroeconomics; bibliometric analysis; complex system.
  
  
• Determinants of government bond returns: an Indian experience  
  by Muhammadriyaj Faniband, Pravin Jadhav 
  Abstract: This paper examines the impact of macroeconomic factors and non-macroeconomic factors on government bond returns in India using quantile regression methodology and the monthly dataset from April 2010 to May 2022. This paper produces a new dataset of three government bonds indices which include the top 20 and top 5 bonds and Treasury Bills (T-Bill). We are the first to document the following results. First, the top 20 and top 5 traded bonds have less sensitivity to the exchange rates. Second, inflation has a negligible impact on the top 20 and T-Bills. Third, all three bonds are significantly affected by interest rates. Fourth, the effect of geopolitical risk is significant on T-Bills. Firth, economic policy uncertainty and volatility do not affect bond returns. Sixth, the Nifty has a significant positive impact on the top 20 and top 5 bonds. Our results are useful for investors, portfolio managers and policymakers.
  Keywords: macroeconomic; non-macroeconomic; government bond; bond returns; quantile regression; India.
  
  
• Worker occupational skills and unemployment duration: a competing-risks econometric approach  
  by Ahmed Wassal Elroukh 
  Abstract: This paper explains differences in unemployment duration among unemployed workers by differences in their skills, using the unemployed workers’ previous occupation and education level to capture their skills. I use the cumulative incidence approach from the statistics literature, which is a better alternative to the standard survival econometric methods in cases of competing risks. In addition to showing that the standard survival econometric methods are biased, I find that the higher the unemployed worker is on the skill ladder based on their previous occupation, the faster their transition rate to a full-time job. An extra year of education has a positive effect on reducing unemployment duration. Those with a bachelor’s degree tend to have the shortest employment duration among all unemployed individuals. However, the impact of education on transitioning from unemployment to a full-time job is less pronounced the higher the unemployed worker’s previous occupation is on the skill ladder.
  Keywords: human capital; unemployment; competing risks; worker skills; duration analysis.
  DOI: 10.1504/IJCEE.2024.10062964
   
  
• Nonlinear autoregressive with exogeneous input neural network time series model performance: bitcoin price prediction  
  by Nurazlina Abdul Rashid, Mohd Tahir Ismail 
  Abstract: There are over 10,000 listed cryptocurrencies, bitcoin has become the most used cryptocurrency at present. This research’s aim is to establish the different dynamic time series architectures of nonlinear autoregressive having exogenous input (NARX) and nonlinear input output (NIO) to forecast the bitcoin price as well as compare their performance. Furthermore, this study attempts to combine the different number of inputs, hidden nodes, and time delay to assess the social media attribute (X) and bitcoin price (Y) past value impact in each model. The results show that all model architectures NARX and NIO with Levenberg-Marquardt backpropagation training algorithm have a significant relationship between inputs and output. That means social dominance, social volume, and weighted social sentiment have a relationship and effect on price except for model 3 with architecture NIO-1-5-1 (d = 1) and NIO 1-10-1 (d = 2). This research is significant because the results of this study will help traders and investors reduce risk and increase returns.
  Keywords: bitcoin; cryptocurrency; price prediction; nonlinear autoregressive with exogeneous input; NARX; neural network time series; dynamic nonlinear; social media; social dominance.
  DOI: 10.1504/IJCEE.2024.10063036
   
  
• New transmission channels of ECB’s unconventional monetary policies  
  by Shuffield Seyram Asafo, Luca Riccetti 
  Abstract: Following the zero-lower bound on interest rates, many central banks turned to increasing the size of their balance sheet to achieve their mandate of price stability and low unemployment. Using the euro area as a case study, we investigate the macroeconomic effects and the transmission channels of the balance sheet expansion by way of a Bayesian VAR model. We identified the BVAR model by imposing sign restrictions on the impulse responses of control variables while leaving our variables of interest unconstrained. We find that the balance sheet expansion caused a higher increase in output than prices. These positive effects were transmitted through the wealth channel, the bank lending channel, and the fiscal channel.
  Keywords: Bayesian VAR; euro area; inflation expectations; unconventional monetary policy; commodity prices.
  DOI: 10.1504/IJCEE.2024.10063204
   
  
• Evaluation and improvement of two homogeneous stock trading systems under computational and experimental finance in China: based on IASM model  
  by Zhuwei Li, Baolu Wang, Rong He 
  Abstract: Artificial simulated stock market model is widely used because it can provide repeatable simulation experiment platform for different trading systems to play a role in the financial market. Based on the investor structure, trading behaviours and institutional rules of Chinese stock market, this paper uses intelligent artificial stock market (IASM) model, aims to build a comprehensive evaluation index system of stock market quality, evaluate the effect of the T + N trading system and the price limit system on the quality of Chinese stock market, and then gives analysis results and improvement suggestions. It is found that T + 0 trading system and narrowing the range of limit price fluctuation can significantly improve the quality of Chinese stock market. At the same time, among the combinations of various T + N trading systems and price limit systems, the combination of T + 0 trading system and 5% price limit system of Chinese stock market has the highest comprehensive quality.
  Keywords: stock trading system; IASM model; market quality evaluation; system improvement; computational and experimental finance.
  DOI: 10.1504/IJCEE.2024.10063567
   
  

Special Issue on: ICOAE2023 Applied Economics and Competition

• Minimum wage as the determinant of productivity in EU countries  
  by Jana Kopecká, Lenka Viskotová, David Hampel 
  Abstract: When introducing and setting minimum wages, primarily to reduce poverty and avoid undesirable phenomena in the labour market, it is necessary to monitor the impact on various aspects of the real economy. This paper focuses on demonstrating the positive impact of nominal minimum wage growth on productivity in EU countries. A cluster analysis is used to divide countries into two distinguished clusters. Using panel regression, the effect of a minimum wage is found to be significant and positive. To rule out spurious regressions and to demonstrate the robustness of the performed analyses, appropriate covariates are included in the models, different forms of productivity are modelled, and the models are also estimated independently for each cluster.
  Keywords: cluster analysis; company production process; EU27; human capital; labour costs; low-wage employees; minimum wage; productivity of labour; panel regression model; training of employees.
  DOI: 10.1504/IJCEE.2024.10062965