Model Selection Procedures in Bounds Test of Cointegration: Theoretical Comparison and Empirical Evidence

Abstract

Only unstructured single-path model selection techniques, i.e., Information Criteria, are used by Bounds test of cointegration for model selection. The aim of this paper was twofold; one was to evaluate the performance of these five routinely used information criteria {Akaike Information Criterion (AIC), Akaike Information Criterion Corrected (AICC), Schwarz/Bayesian Information Criterion (SIC/BIC), Schwarz/Bayesian Information Criterion Corrected (SICC/BICC), and Hannan and Quinn Information Criterion (HQC)} and three structured approaches (Forward Selection, Backward Elimination, and Stepwise) by assessing their size and power properties at different sample sizes based on Monte Carlo simulations, and second was the assessment of the same based on real economic data. The second aim was achieved by the evaluation of the long-run relationship between three pairs of macroeconomic variables, i.e., Energy Consumption and GDP, Oil Price and GDP, and Broad Money and GDP for BRICS (Brazil, Russia, India, China and South Africa) countries using Bounds cointegration test. It was found that information criteria and structured procedures have the same powers for a sample size of 50 or greater. However, BICC and Stepwise are better at small sample sizes. In the light of simulation and real data results, a modified Bounds test with Stepwise model selection procedure may be used as it is strongly theoretically supported and avoids noise in the model selection process.

The missing link between wages and labour productivity in tourism: evidence from Croatia and Slovenia

“…Arandarenko and Vukojevic (2008) stated that formality and informality do not appear as binary choice, but rather along a spectrum of statuses, from full informality through semi-formality (tourism industry with sharing services, selfemployment, double payrolls in many small private firms), to full formality most typically in the public sector. The availability of secondary data can represent limitations for research (Badshah & Bulut, 2020;Dogru & Bulut, 2018;Guli c, 2018;Hall, 2002;Yalçinkaya et al, 2018). Finally, quality in tourism services cannot be measured merely by the number of stars, or by investment in infrastructure.…”

“…which are included in cointegration analysis, ECM and VAR model; and variables are at most $ Ið2Þ: Therefore, the empirical part includes data sets from Equation ( 9) presented in four steps: first, summary statistics and visual inspection; second, Granger Causality test; third, ECM; and fourth, VAR and VECM following theoretical considerations (Brooks, 2019) and empirical approaches (Badshah & Bulut, 2020;Tang, 2010Tang, , 2012Tang, , 2014.…”

The Impact of Foreign Capital Inflows on Agriculture Development and Poverty Reduction: Panel Data Analysis for Developing Countries

“…To check the robustness of the established models, we applied other lag criterion, such as the Schwarz Bayesian information criterion (SBC) and the Hannan-Quinn criterion (HQ), which applicability to testing the robustness of economic variables in developing countries has been demonstrated by many scholars, including by Aronu et al [97] in Nigeria, Aslam and Lebbe [98] in Sri Lanka, Iqbal Chaudhry et al [99] in China, Mehrara [100] in Iran, and Badshah and Bulut [101] in BRICS countries. We found that results had no change with the sign and significance of the coefficients.…”

Sustainable Food Value Chains: Approaches to Transaction Costs in Agro-Alimentary Systems of Developing Countries—A Chile Case Study

“…Daily price determination and diverse delivery options inherent in these markets lead to arbitrage opportunities. The increasing focus on sustainability in food supply chains, driven by various stakeholders, necessitates industry and retail assessment and enhancement of environmental and social performance [2]. Establishing sustainable supply chains is crucial for future competitiveness and stakeholder approval.…”