The education bias of 'trade liberalization' and wage inequality in developing countries

The aim of this paper is to examine the impact of increased trade on wage inequality in developing countries, and whether a higher human capital stock moderates this effect. We look at the skilled-unskilled wage differential. High initial endowments of human capital imply a more egalitarian society. When more equal societies open up their economies further, increased trade is likely to induce less inequality on impact because the supply of skills better matches demand. But greater international exposure also brings about technological diffusion, further raising skilled labour demand. This may raise wage inequality, in contrast to the initial egalitarian level effect of human capital. We attempt to measure these two opposing forces. We also employ a broad set of openness indicators to measure trade liberalization policies as well as general openness, which is an outcome, and not a policy variable. We further examine what type of education most reduces inequality. Our findings suggest that countries with a higher level of initial human capital do well on the inequality front, but human capital which accrues through the trade liberalization channel has inegalitarian effects. One explanation could be that governments in developing countries invest more in higher education at the expense of primary education in order to gain immediate benefits from globalization; thus becoming prone to wage inequality after increased international trade. Our results also have implications for the speed at which trade policies are liberalized, the implication being that better educated nations should liberalize faster

When Education Explains Strong Institutions: Trade Policy also Matters

This paper empirically examines the contribution of trade liberalisation to differences in the level of prosperity across nations. We compare this with the relative contribution of institutional capacity to prosperity, as well as the role of human capital accumulation in that respect. We employ several concepts of institutional quality, trade policy and openness variables following various definitions prevalent in the literature. Unlike in the comparable study by Rodrik et al. (2004) we have (a) included a role for human capital, (b) employed six institutional variables compared to one only in Rodrik et al. (rule of law), (c) included trade policy variables, and not just openness indicators and (d) expanded the set of openness measures employed. We discover that opening up domestic markets to foreign competition by removing trade restrictions and barriers may promote economic performance. Furthermore, developing human capital is as important as superior institutional functioning for economic wellbeing. We find that openness counts for little per se in explaining income differences across countries. This is because it is an outcome and not a cause. Trade policies, and liberalisation, on the other hand, are not insignificant in explaining cross-country per-capita income variation. With regard to trade policies, export taxes are the most important in explaining cross-country per-capita income differences

Predictive Analysis of Students’ Learning Performance Using Data Mining Techniques: A Comparative Study of Feature Selection Methods

The utilization of data mining techniques for the prompt prediction of academic success has gained significant importance in the current era. There is an increasing interest in utilizing these methodologies to forecast the academic performance of students, thereby facilitating educators to intervene and furnish suitable assistance when required. The purpose of this study was to determine the optimal methods for feature engineering and selection in the context of regression and classification tasks. This study compared the Boruta algorithm and Lasso regression for regression, and Recursive Feature Elimination (RFE) and Random Forest Importance (RFI) for classification. According to the findings, Gradient Boost for the regression part of this study had the least Mean Absolute Error (MAE) and Root-Mean-Square Error (RMSE) of 12.93 and 18.28, respectively, in the case of the Boruta selection method. In contrast, RFI was found to be the superior classification method, yielding an accuracy rate of 78% in the classification part. This research emphasized the significance of employing appropriate feature engineering and selection methodologies to enhance the efficacy of machine learning algorithms. Using a diverse set of machine learning techniques, this study analyzed the OULA dataset, focusing on both feature engineering and selection. Our approach was to systematically compare the performance of different models, leading to insights about the most effective strategies for predicting student success

On the Costs of Not Loving Thy Neighbour as Thyself

The authors examine whether greater inter-state trade, democracy and reduced military spending lower belligerence between India and Pakistan. They begin with theoretical models covering the opportunity costs of conflict in terms of trade losses and security spending, as well as the costs of making concessions to rivals. Conflict between the two nations can be best understood in a multivariate framework where variables such as economic performance, integration with rest of the world, bilateral trade, military expenditure, population are simultaneously taken into account. The authors' empirical investigation based on time series econometrics for the period 1950-2005 with causality tests suggests that reduced trade, greater military expenditure, less development expenditure, lower levels of democracy, lower growth rates and less general trade openness are all conflict enhancing. Moreover, there is reverse causality between bilateral trade, militarization and conflict; low levels of bilateral trade and high militarization are conflict enhancing, equally conflict also reduces bilateral trade and raises militarization. The authors also run forecasting simulations on 6 different VECM models. Globalization or a greater openness to international trade in general are more significant drivers of a liberal peace, rather than a common democratic political orientation suggested by the pure form of the democratic peace