Template-Type: ReDIF-Article 1.0 Author-Name: Federico Brogi Author-X-Name-First: Federico Author-X-Name-Last: Brogi Author-Name: Barbara Guardabascio Author-X-Name-First: Barbara Author-X-Name-Last: Guardabascio Author-Name: Giulio Barcaroli Author-X-Name-First: Giulio Author-X-Name-Last: Barcaroli Title: The management of COVID-19 epidemic: estimate of the actual infected population, impact of social distancing and directions for an efficient testing strategy. The case of Italy Abstract: This work focuses on the so called 'first wave' of COVID-19 epidemic (21 February-10 April 2020) and aims at outlining a viable strategy to contain the COVID-19 spread and efficiently plan an exit from lockdown measures. It offers a model to estimate the total number of actual infected among the population at national and regional level inferring from the lethality rate, to fill the proven gap with the number of officially reported cases. The result is the reference population used to develop a forecasting exercise of new daily cases, compared to the reported ones. The eventual discrepancy is analysed in terms of compliance with the restrictive measures or to an insufficient number of tests performed. This simulation indicates that an efficient testing policy is the main actionable measure. Furthermore, the paper estimates the optimal number of tests to be performed at national and regional level, in order to be able to release an increasing number of individuals from restrictive measures. Journal: Int. J. of Computational Economics and Econometrics Pages: 342-365 Issue: 4 Volume: 12 Year: 2022 Keywords: COVID-19; policy evaluation; scenario analysis; infected population; testing strategy; compliance; Italy. File-URL: http://www.inderscience.com/link.php?id=126311 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:4:p:342-365 Template-Type: ReDIF-Article 1.0 Author-Name: Christopher F. Baum Author-X-Name-First: Christopher F. Author-X-Name-Last: Baum Author-Name: Miguel Henry Author-X-Name-First: Miguel Author-X-Name-Last: Henry Title: Socio-economic and demographic factors influencing the spatial spread of COVID-19 in the USA Abstract: As the COVID-19 pandemic progressed in the USA, 'hotspots' shifted geographically over time to suburban and rural counties showing a high prevalence of the disease. We analyse population-adjusted confirmed case rates based on daily US county-level variations in COVID-19 confirmed case counts during the first several months of the pandemic (1 March 2020 through 23 May 2020) to evaluate the spatial dependence between neighbouring counties and quantify the overall spatial effect of socio-economic and demographic factors on the prevalence of COVID-19. We indeed find strong evidence of county-level socio-economic and demographic factors influencing the spatial spread such as sex, race, ethnicity, population density, pollution, health conditions, and income. The relevance of the spatial factors suggests that neighbouring counties have a significant and positive effect on the prevalence of COVID-19. Journal: Int. J. of Computational Economics and Econometrics Pages: 366-380 Issue: 4 Volume: 12 Year: 2022 Keywords: COVID-19; coronavirus; spatial spillovers; socio-economic factors; demographics; spatial econometrics. File-URL: http://www.inderscience.com/link.php?id=126313 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:4:p:366-380 Template-Type: ReDIF-Article 1.0 Author-Name: Dinesh K. Sharma Author-X-Name-First: Dinesh K. Author-X-Name-Last: Sharma Author-Name: H.S. Hota Author-X-Name-First: H.S. Author-X-Name-Last: Hota Author-Name: Vineet Kumar Awasthi Author-X-Name-First: Vineet Kumar Author-X-Name-Last: Awasthi Title: An integrated K-means-GP approach for US stock fund diversification and its impact due to COVID-19 Abstract: The stock fund diversification process is a tedious task due to the erratic nature of the stock market. On the other hand, work is more challenging due to high annual return expectations with low risk. This research work explores the potential of goal programming (GP) and K-means algorithm as an integrated K-means-GP approach for fund diversification, where K-means is used to create groups of stock based on their performance. Then GP is used to diversify total funds into various groups of stocks to achieve a high annual return. The experimental work has been done in 30 stocks of DOW30 of the years 2017-2018, 2018-2019, and 2019-2020. A comparative study was carried with three different cases based on individual year data and an average of two and three years of data. The empirical results show that: the K-means-GP approach outperformed the GP approach for stock fund diversification; the annual return is higher in the case of the K-means-GP approach using three years of average data with 12.59% of annual return against the expected annual return of 20%. Due to COVID-19, few stocks perform in the negative direction, and hence the annual return is being affected after fund diversification. Journal: Int. J. of Computational Economics and Econometrics Pages: 381-404 Issue: 4 Volume: 12 Year: 2022 Keywords: k-means; goal programming; DOW30; fund diversification; COVID-19. File-URL: http://www.inderscience.com/link.php?id=126317 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:4:p:381-404 Template-Type: ReDIF-Article 1.0 Author-Name: Robert L. Grant Author-X-Name-First: Robert L. Author-X-Name-Last: Grant Title: Non-parametric Bayesian updating and windowing with kernel density and the kudzu algorithm Abstract: The concept of 'updating' parameter estimates and predictions as more data arrive is an important attraction for people adopting Bayesian methods, and essential in big data settings. Implementation via the hyperparameters of a joint prior distribution is challenging. This paper considers non-parametric updating, using a previous posterior sample as a new prior sample. Streaming data can be analysed in a moving window of time by subtracting old posterior sample(s) with appropriate weights. We evaluate three forms of kernel density, a sampling importance resampling implementation, and a novel algorithm called kudzu, which smooths density estimation trees. Methods are tested for distortion of illustrative prior distributions, long-run performance in a low-dimensional simulation study, and feasibility with a realistically large and fast dataset of taxi journeys. Kernel estimation appears to be useful in low-dimensional problems, and kudzu in high-dimensional problems, but careful tuning and monitoring is required. Areas for further research are outlined. Journal: Int. J. of Computational Economics and Econometrics Pages: 405-428 Issue: 4 Volume: 12 Year: 2022 Keywords: Bayesian data analysis; big data; density estimation trees; kernel density estimation; non-parametric statistics; streaming data. File-URL: http://www.inderscience.com/link.php?id=126320 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:4:p:405-428 Template-Type: ReDIF-Article 1.0 Author-Name: Shira Fano Author-X-Name-First: Shira Author-X-Name-Last: Fano Author-Name: Gianluca Toschi Author-X-Name-First: Gianluca Author-X-Name-Last: Toschi Title: COVID-19 pandemic and the economy: sentiment analysis on Twitter data Abstract: In the last decade, social networks have increasingly been used in social sciences to monitor consumer preferences and citizens' opinion formation, as they are able to produce a massive amount of data. In this paper, we aim to collect and analyse data from Twitter posts identifying emerging patterns related to the COVID-19 outbreak and to evaluate the economic sentiment of users during the pandemic. Using the Twitter API, we collected tweets containing the term coronavirus and at least a keyword related to the economy selected from a pre-determined batch, obtaining a database of approximately two million tweets. We show that our Economic Twitter Index (ETI) is able to nowcast the current state of economic sentiment, exhibiting peaks and drops related to real-world events. Finally, we test our index and it shows a positive correlation to standard economic indicators. Journal: Int. J. of Computational Economics and Econometrics Pages: 429-444 Issue: 4 Volume: 12 Year: 2022 Keywords: economic sentiment index; sentiment analysis; COVID-19 pandemic; Twitter; social media. File-URL: http://www.inderscience.com/link.php?id=126322 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:4:p:429-444 Template-Type: ReDIF-Article 1.0 Author-Name: Paolo Brunori Author-X-Name-First: Paolo Author-X-Name-Last: Brunori Author-Name: Giuliano Resce Author-X-Name-First: Giuliano Author-X-Name-Last: Resce Author-Name: Laura Serlenga Author-X-Name-First: Laura Author-X-Name-Last: Serlenga Title: Searching for the peak: Google Trends and the first COVID-19 wave in Italy Abstract: One of the difficulties faced by policymakers during the COVID-19 outbreak in Italy was the monitoring of the virus diffusion. Due to changes in the criteria and insufficient resources to test all suspected cases, the number of 'confirmed infected' rapidly proved to be unreliably reported by official statistics. We explore the possibility of using information obtained from Google Trends to predict the evolution of the epidemic. Following the most recent developments on the statistical analysis of longitudinal data, we estimate a dynamic heterogeneous panel. This approach allows to takes into account the presence of common shocks and unobserved components in the error term both likely to occur in this context. We find that Google queries contain useful information to predict number patients admitted to the intensive care units, number of deaths and excess mortality in Italian regions. Journal: Int. J. of Computational Economics and Econometrics Pages: 445-458 Issue: 4 Volume: 12 Year: 2022 Keywords: COVID-19; Google Trends; dynamic panel data; Italy. File-URL: http://www.inderscience.com/link.php?id=126323 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:4:p:445-458 Template-Type: ReDIF-Article 1.0 Author-Name: Israa A. El Husseiny Author-X-Name-First: Israa A. El Author-X-Name-Last: Husseiny Author-Name: Mohamed M. Badawy Author-X-Name-First: Mohamed M. Author-X-Name-Last: Badawy Title: Evaluating the efficiency of fiscal responses to COVID-19 pandemic in the OECD countries: a two-stage data envelopment analysis approach Abstract: This study examines the relative technical efficiency (TE) of the fiscal stimulus packages introduced by the governments of 38 OECD countries in response to COVID-19 pandemic, using a two-stage data envelopment analysis (DEA) approach. The DEA results indicate that OECD countries are inefficient as they have the potential to save around 54.8% of their fiscal packages while maintaining the same performance in terms of economic growth and unemployment. Costa Rica, Greece, Ireland, Italy, Mexico, and Turkey are found to be fully efficient whereas Canada, Germany, Japan, the USA, and the UK are found to be the least efficient. The Tobit findings indicate that belonging to the EU, public expenditure on education, and population density, are positively correlated to the TE scores. In contrary, general government final consumption expenditure, size of fiscal stimulus packages, and COVID-19 infections rate tend to affect efficiency negatively. Journal: Int. J. of Computational Economics and Econometrics Pages: 459-485 Issue: 4 Volume: 12 Year: 2022 Keywords: COVID-19; fiscal packages; economic growth; unemployment; data envelopment analysis; DEA; Tobit; OECD. File-URL: http://www.inderscience.com/link.php?id=126325 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:4:p:459-485 Template-Type: ReDIF-Article 1.0 Author-Name: Bernard Fingleton Author-X-Name-First: Bernard Author-X-Name-Last: Fingleton Title: Exploring Brexit implications: the impact of longer journey times 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. Journal: Int. J. of Computational Economics and Econometrics Pages: 174-196 Issue: 1/2 Volume: 12 Year: 2022 Keywords: Brexit; journey times; dynamic spatial panel model; regional employment. File-URL: http://www.inderscience.com/link.php?id=120496 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:1/2:p:174-196 Template-Type: ReDIF-Article 1.0 Author-Name: Antonio Zinilli Author-X-Name-First: Antonio Author-X-Name-Last: Zinilli Author-Name: Andrea Orazio Spinello Author-X-Name-First: Andrea Orazio Author-X-Name-Last: Spinello Author-Name: Emanuela Reale Author-X-Name-First: Emanuela Author-X-Name-Last: Reale Title: Transnational public research funding in Europe: exploring proximity dimensions in the ERA-NET programs 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 mobilising 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 programs. The research question is investigated by analysing JoREP 2.0, a database containing data on the organisational and financial characteristics of transnational joint research programs 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 programs, such as ERA-NETs. Journal: Int. J. of Computational Economics and Econometrics Pages: 52-73 Issue: 1/2 Volume: 12 Year: 2022 Keywords: public research funding; ERA-NET; proximity; spatial statistics. File-URL: http://www.inderscience.com/link.php?id=120498 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:1/2:p:52-73 Template-Type: ReDIF-Article 1.0 Author-Name: Edmondo Di Giuseppe Author-X-Name-First: Edmondo Di Author-X-Name-Last: Giuseppe Author-Name: Gianfranco Giulioni Author-X-Name-First: Gianfranco Author-X-Name-Last: Giulioni Author-Name: Massimiliano Pasqui Author-X-Name-First: Massimiliano Author-X-Name-Last: Pasqui Title: Simulating the effect of El Niño Southern Oscillation on the worldwide wheat prices Abstract: This work analyses the impact of the large-scale atmospheric-oceanic phenomenon known as El Niño Southern Oscillation on wheat production, and the consequent changes in prices at the global scale by using computer simulations. Several intermediate results are obtained on the way to the final goal. The identification of geographic areas relevant to the international wheat market and the integration of heterogeneous datasets are two of them. Building on these two results, the local effects of the El Niño Southern Oscillation phases on the wheat yield are quantified using robust ANOVA regression, and their potential impacts on the aggregate production of each area are estimated. Finally, these estimates are provided as inputs to the computational model, which outputs, among others, the wheat prices of 12 internationally relevant production areas. Simulation results show how the cross-section distributions of prices, conditional on the occurring of El Niño and La Niña, spread to the right compared to that observed for the neutral phase. Therefore, both non-neutral phases imply an increase of average and dispersion of prices, although the effect of La Niña is weaker than that of El Niño. Journal: Int. J. of Computational Economics and Econometrics Pages: 105-138 Issue: 1/2 Volume: 12 Year: 2022 Keywords: computational model? wheat international markets? climate variability? robust ANOVA regression? price cross-section distributions. File-URL: http://www.inderscience.com/link.php?id=120502 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:1/2:p:105-138 Template-Type: ReDIF-Article 1.0 Author-Name: Alexios Makropoulos Author-X-Name-First: Alexios Author-X-Name-Last: Makropoulos Author-Name: Charlie Weir Author-X-Name-First: Charlie Author-X-Name-Last: Weir Author-Name: Xin Zhang Author-X-Name-First: Xin Author-X-Name-Last: Zhang Title: Does spatial location affect business liquidations? 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. Journal: Int. J. of Computational Economics and Econometrics Pages: 139-157 Issue: 1/2 Volume: 12 Year: 2022 Keywords: business failure; liquidations; spatial effects; European countries. File-URL: http://www.inderscience.com/link.php?id=120503 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:1/2:p:139-157 Template-Type: ReDIF-Article 1.0 Author-Name: Anuphak Saosaovaphak Author-X-Name-First: Anuphak Author-X-Name-Last: Saosaovaphak Author-Name: Chukiat Chaiboonsri Author-X-Name-First: Chukiat Author-X-Name-Last: Chaiboonsri Author-Name: Satawat Wannapan Author-X-Name-First: Satawat Author-X-Name-Last: Wannapan Title: Causal statistics of structural dependence space-based trend simulations for the coalition of rice exporters: the cases of India, Thailand, and Vietnam 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. Optimised results causally prove that rice exporting profits are a double increment when cooperative behaviours continuously exist. Hence, the potential outcomes framework is to finally recognise the Organization of Rice Exporting Countries (OREC). Journal: Int. J. of Computational Economics and Econometrics Pages: 4-28 Issue: 1/2 Volume: 12 Year: 2022 Keywords: rice exports; Bayesian copulas; Bayesian structural time-series analysis; Shapley value; coalition game. File-URL: http://www.inderscience.com/link.php?id=120504 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:1/2:p:4-28 Template-Type: ReDIF-Article 1.0 Author-Name: Ebru Caglayan-Akay Author-X-Name-First: Ebru Author-X-Name-Last: Caglayan-Akay Author-Name: Fulden Komuryakan Author-X-Name-First: Fulden Author-X-Name-Last: Komuryakan Title: The effects of education and experience on youth employee wages: the case of Turkey 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 by estimating the extended Mincer wage equation with robust estimators to respond to the research questions. The findings show that postgraduate and bachelor's 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. Journal: Int. J. of Computational Economics and Econometrics Pages: 158-173 Issue: 1/2 Volume: 12 Year: 2022 Keywords: Mincer; youth labour market; wage equation; robust regression; S; MM; Turkey. File-URL: http://www.inderscience.com/link.php?id=120508 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:1/2:p:158-173 Template-Type: ReDIF-Article 1.0 Author-Name: Raffaele Spallone Author-X-Name-First: Raffaele Author-X-Name-Last: Spallone Author-Name: Giovanni Cerulli Author-X-Name-First: Giovanni Author-X-Name-Last: Cerulli Title: A dose response evaluation of regional incentives to R%D 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 analyse 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). Journal: Int. J. of Computational Economics and Econometrics Pages: 74-104 Issue: 1/2 Volume: 12 Year: 2022 Keywords: state aid; evaluation; research and development; R%D incentives. File-URL: http://www.inderscience.com/link.php?id=120509 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:1/2:p:74-104 Template-Type: ReDIF-Article 1.0 Author-Name: Chukiat Chaiboonsri Author-X-Name-First: Chukiat Author-X-Name-Last: Chaiboonsri Author-Name: Satawat Wannapan Author-X-Name-First: Satawat Author-X-Name-Last: Wannapan Author-Name: Nisit Pantamit Author-X-Name-First: Nisit Author-X-Name-Last: Pantamit Title: Perspective of an exchange rate policy for global financial systems: evidence between China and ASEAN countries 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 empirical currencies' structural dependences. The relationships between RMB Chinese Yuan and ASEAN currencies are thus computationally analysed. Our approach structurally classifies the flows and impulse responses activated by currency appreciation and depreciation. Additionally, agent-based simulations are carried out to depict systematically economic scenarios under currency fluctuation, thus providing suitable alerts for decision-makers when dangerous outlooks concerning trade dynamics in Indochina take place. Journal: Int. J. of Computational Economics and Econometrics Pages: 29-51 Issue: 1/2 Volume: 12 Year: 2022 Keywords: exchange rates; macroeconomics; economic extreme cases; copulas; agent-based analysis; Monte Carlo simulation; China; ASEAN. File-URL: http://www.inderscience.com/link.php?id=120510 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:1/2:p:29-51 Template-Type: ReDIF-Article 1.0 Author-Name: Olusola Joel Oyeleke Author-X-Name-First: Olusola Joel Author-X-Name-Last: Oyeleke Author-Name: Lukman O. Oyelami Author-X-Name-First: Lukman O. Author-X-Name-Last: Oyelami Author-Name: Adeyemi A. Ogundipe Author-X-Name-First: Adeyemi A. Author-X-Name-Last: Ogundipe Title: Investigating the monetary and fiscal policy regimes dominance for inflation determination in Nigeria: a Bayesian TVP-VAR analysis 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 co-integration 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 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. Journal: Int. J. of Computational Economics and Econometrics Pages: 223-240 Issue: 3 Volume: 12 Year: 2022 Keywords: Bayesian TVP-VAR; co-integration; determination; dominance; fiscal policy; monetary policy; Nigeria; impulse response functions; inflation. File-URL: http://www.inderscience.com/link.php?id=122829 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:3:p:223-240 Template-Type: ReDIF-Article 1.0 Author-Name: Oznur Ozdamar Author-X-Name-First: Oznur Author-X-Name-Last: Ozdamar Author-Name: Sibel Gunduz Author-X-Name-First: Sibel Author-X-Name-Last: Gunduz Author-Name: Eleftherios Giovanis Author-X-Name-First: Eleftherios Author-X-Name-Last: Giovanis Title: The effect of female employment on saving-investment gap and the role of their interaction in the economic growth 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. Journal: Int. J. of Computational Economics and Econometrics Pages: 241-262 Issue: 3 Volume: 12 Year: 2022 Keywords: developing economies; economic growth; female employment rate; gender roles; gender inequalities; gender-wage gap; low and middle income countries; panel cross-section dependence test; panel data analysis; saving-investment gap; social norms; unit root tests. File-URL: http://www.inderscience.com/link.php?id=122830 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:3:p:241-262 Template-Type: ReDIF-Article 1.0 Author-Name: Panagiotis Tachinakis Author-X-Name-First: Panagiotis Author-X-Name-Last: Tachinakis Title: Tax benefits determinants and earnings management: results from the eurozone countries 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. Journal: Int. J. of Computational Economics and Econometrics Pages: 263-274 Issue: 3 Volume: 12 Year: 2022 Keywords: earnings management; tax havens; tax revenue. File-URL: http://www.inderscience.com/link.php?id=122831 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:3:p:263-274 Template-Type: ReDIF-Article 1.0 Author-Name: Dimitrios Dadakas Author-X-Name-First: Dimitrios Author-X-Name-Last: Dadakas Title: A SAS macro for examining stationarity under the presence of up to m endogenous structural breaks with an application on EU28 agri-food exports Abstract: I present a SAS macro that allows the examination of stationarity under the presence of up to <i>m</i>, 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 agri-food products, HS categories 1 through 24. The code prepares a report of the results in PDF format. Journal: Int. J. of Computational Economics and Econometrics Pages: 275-283 Issue: 3 Volume: 12 Year: 2022 Keywords: endogenous structural breaks; stationarity; time series; SAS; macro. File-URL: http://www.inderscience.com/link.php?id=122833 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:3:p:275-283 Template-Type: ReDIF-Article 1.0 Author-Name: Per Bjarte Solibakke Author-X-Name-First: Per Bjarte Author-X-Name-Last: Solibakke Title: Bootstrapped nonlinear impulse-response analysis: the FTSE100 (UK) and the NDX100 (US) indices 2012-2021 Abstract: This paper presents bootstrapped nonlinear impulse response function analyses for general step ahead mean and volatility densities. From strictly (ergodic and) stationary series and BIC optimal nonlinear model coefficients, the paper establishes step-ahead densities for both the conditional mean and volatility. For sampling variances using one thousand samples and conditioning all paths on the daily impulses -5, -3, ..., 5% all mean and volatility responses show mean reversion. For the volatility, all increases seem to arise from negative index movements suggesting strong asymmetry. Furthermore, the model coefficients for the volatility exhibit data dependence suggesting ability to predict volatility. The indices report some striking step-ahead differences for both the mean and the volatility. For the mean, only the NDX100 seems to show overreactions. For the volatility, for both positive and negative impulses the NDX100 reports higher volatility responses then FTSE100. However, asymmetry manifested for both indices suggesting that trading volatility as an asset may insure against market crashes and be an excellent diversification instrument. Finally, using a stochastic volatility model to obtain calibrated functions that give step-ahead predicted values for static predictions, enriches participants' derivative trading strategies (i.e., volatility swaps). Journal: Int. J. of Computational Economics and Econometrics Pages: 197-221 Issue: 1/2 Volume: 12 Year: 2022 Keywords: bootstrapping; conditional heteroscedasticity; equity markets; impulse-response functions; nonlinearity; volatility predictions. File-URL: http://www.inderscience.com/link.php?id=120531 File-Format: text/html File-Restriction: Open Access Handle: RePEc:ids:ijcome:v:12:y:2022:i:1/2:p:197-221 Template-Type: ReDIF-Article 1.0 Author-Name: Engin Tas Author-X-Name-First: Engin Author-X-Name-Last: Tas Author-Name: Ayca Hatice Atli Author-X-Name-First: Ayca Hatice Author-X-Name-Last: Atli Title: A comparison of SVR and NARX in financial time series forecasting Abstract: Machine learning techniques have become attractive due to their robustness and superiority in predicting future behaviour in various areas. This paper is aimed to predict future stock prices by applying a nonlinear 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. Journal: Int. J. of Computational Economics and Econometrics Pages: 303-320 Issue: 3 Volume: 12 Year: 2022 Keywords: artificial learning; artificial neural networks; financial time series forecasting; nonlinear autoregressive network with exogenous inputs; NARX; support vector regression; SVR. File-URL: http://www.inderscience.com/link.php?id=122835 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:3:p:303-320 Template-Type: ReDIF-Article 1.0 Author-Name: Sebastián Nicolsás González Author-X-Name-First: Sebastián Nicolsás Author-X-Name-Last: González Author-Name: Carlos Adrián Romero Author-X-Name-First: Carlos Adrián Author-X-Name-Last: Romero Author-Name: María Priscila Ramos Author-X-Name-First: María Priscila Author-X-Name-Last: Ramos Author-Name: Pablo Augusto Negri Author-X-Name-First: Pablo Augusto Author-X-Name-Last: Negri Author-Name: Matias Marino Author-X-Name-First: Matias Author-X-Name-Last: Marino Title: The App-RegMIP: an open access software for regional input-output tables estimation Abstract: To extend automatic regionalisation of a national input-output (IO) matrix we developed an (online and desk version) open access software tool, the App-RegMIP, which applies location quotients methods for regional coefficients estimations (FLQ, AFLQ). By considering a national IO matrix and sectoral gross outputs of the regions of interest, this software makes it possible to compute a first approximation of regional IO matrices in an easy and tractable way. These RIO matrices are the basic inputs for regional interindustry structure analysis, as illustrated by the case study of an Argentine Province. The App-RegMIP is thus a useful tool for the process of regional data generation and the first of its kind that is open access. Further extensions of this software could be the inclusion of other methods of regionalisation and matrices calibration methods, and the computation of multipliers and analytical indicators that can contribute to researchers' studies and policy-makers' decisions. Journal: Int. J. of Computational Economics and Econometrics Pages: 284-302 Issue: 3 Volume: 12 Year: 2022 Keywords: non-survey techniques; regional input-output tables; location quotients methods; regionalisation open-access software; App-RegMIP; Argentina Province case study. File-URL: http://www.inderscience.com/link.php?id=122836 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:3:p:284-302 Template-Type: ReDIF-Article 1.0 Author-Name: Khyati Chopra Author-X-Name-First: Khyati Author-X-Name-Last: Chopra Author-Name: M. Afshar Alam Author-X-Name-First: M. Afshar Author-X-Name-Last: Alam Title: Stackelberg secure modelling game scheme for price-power control in cognitive radio enabled agriculture system Abstract: The smart 'internet of things' (IoT)-based farming is capable of capturing the sensed information and then transmitting it to the user in a cooperative cognitive radio (CCR) network. CCR has emanated as a dynamic spectrum access technique, where the powers of secondary users (SUs) are controlled such that the quality of service of primary communication is unaffected. Due to dynamic and broadcast nature of cognitive networks, the sensor devices can be controlled and monitored from remote location, but are vulnerable to attack by an unauthorised user. In this paper, we have proposed a Stackelberg game secure model for power trading in CCR network to improve the system performance and stimulate cooperation. A leader-follower scenario is set up where; the relay or leader node is trading power to source or follower node. The utilities of both source and relay are maximised and an optimal solution is obtained using convex optimisation method. Journal: Int. J. of Computational Economics and Econometrics Pages: 321-338 Issue: 3 Volume: 12 Year: 2022 Keywords: cognitive radio; decode-forward relay; intercept probability; Stackelberg game; Nash equilibrium; cooperative cognitive radio; CCR; quality of service; QoS; internet of things; IoT. File-URL: http://www.inderscience.com/link.php?id=122837 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijcome:v:12:y:2022:i:3:p:321-338