Economic Literacy amongst the Secondary School Teachers in Perak Malaysia

The aim of the study is to determine the relationship between economics education exposure, saving, expenditure, investment and economics literacy amongst teachers in secondary schools in Perak. The theoretical framework was designed based on the literature and hence five hypotheses for the study were formulated. The samples were selected by quota sampling methods. The data were collected by distributing structured 35 items questionnaires to 100 teachers in secondary schools in eight districts in Perak. The instrument was adapted form Leader Behaviour Description Questionnaires which were used to measure economic literacy. Only 60 questionnaires were returned and analysed which gave 60% respond rate. Data collected were sorted out and keyed in into SPSS version 17. The data were analysed using descriptive and inferential statistics to answer the research questions. The result of the analyses showed that there was significant relationship between economics education and its predictors. Together the independent variables explained 81.7% of the variance in the dependent variables. The remaining 18.3% was due to unidentified variables. In relation to that, the study had contributed some knowledge about the understanding of economic of literacy. For future research, it is recommended that other than the above variables might influence economic literacy perhaps with a bigger samples and wider scope

The incidence and the effect of overskilling on individuals’ wages in Malaysia: a quantile regression approach

This paper examines the incidence and the effect of overskilling on wages by taking individuals’ unobserved heterogeneity in ability using quantile regression (QR) method. Using data from the second Malaysia Productivity and Investment Climate Survey (PICS-2), the incidence of overskilling was reported around 31 percent - for which moderately overskilled accounted for 23 percent and severely overskilled accounted for 8 percent. Preliminary analysis revealed that overskilling was found to be heavily concentrated within low-ability segments of the workers’ conditional wage distributions. Using quantile regression (QR) method, the results revealed that although being overskilled resulted in wage penalty, the penalty, however, was heterogeneous across the entire workers’ conditional wages distribution. Indeed, the penalty for moderately overskilled was greater at the lower deciles and became smaller or even disappears as one moved up the wages distribution. This may be consistent with the view that the overskilled workers are likely amongst the lowability workers. By contrast, the penalty for severely overskilled, in particular women was evident all the way through the conditional wage distribution. This perhaps suggests that unobserved heterogeneity unable to explain the wages penalty for mismatched women. Nevertheless, this study may suggest the importance of including explicit controls for individuals’ unobserved ability where possible, as a mean to avoid bias estimation of the wage impacts of the overskilling

Stock price movements : does change in energy price matter?

This paper investigates the impact of oil price shocks on the Malaysian stock market. The co-integration test results documented zero co-integration equation. This finding implies no long-run relationship between the variables in the system. The causality test which looks at short run dynamic interactions between the variables also documented the same finding where shocks in all types of oil prices do not impose any effect on movements in stock price. This finding leads us to conclude that, a change in oil price(s) has no significant effect on stock market both in the short-run and longrun. These findings also lead us to conclude thaPt, change in oil price, particularly domestic oil price1 cannot be used as a policy tool in adjusting the stock market in any case shocks in oil price strike again in future

The Investigation of Job Search Behaviour Among Workers in the Manufacturing Sector in Malaysia: Do Education and Skill Mismatch Matter

This paper investigates the influence of education and skill mismatch on job search behaviour and quits intention among workers in the manufacturing sector in Malaysia. Three indicators of mismatch were employed here; over-education, overskilling and job mismatch and they were measured using workers’ own assessment. Using data from own field survey, the 2016 Co-workers’ Externalities at Workplace (TERS-16), it was found that 18%, 45% and 37% of respondents were deemed overeducated, overskilled and being in mismatched jobs, respectively. Using random effect probit models, three main findings were observed. As expected, there was strong evidence that overqualification resulted in job search activity. Being in jobs that completely different from workers’ actual field of study also increased the likelihood of seeking new jobs relative to the reference group. Finally, being overskilled also led to a higher probability of being engaged in job search behaviour. Interestingly, the magnitude of the effect was twice higher for the severely than for the moderately-overskilled. These findings were robust even after all education-skill mismatch indicators were controlled for together. The results of the study reflect greater potential mobility amongst the mismatched workers in Malaysia. There is impossible to ascertain whether or not such a move results in improved matches due to data limitation. Yet, from a firm’s perspective, higher intensity of job search behaviour among the mismatched may lead to a higher turnover rate and incur hiring and training cost.

Predicting automobile insurance fraud using classical and machine learning models

Insurance fraud claims have become a major problem in the insurance industry. Several investigations have been carried out to eliminate negative impacts on the insurance industry as this immoral act has caused the loss of billions of dollars. In this paper, a comparative study was carried out to assess the performance of various classification models, namely logistic regression, neural network (NN), support vector machine (SVM), tree augmented naïve Bayes (NB), decision tree (DT), random forest (RF) and AdaBoost with different model settings for predicting automobile insurance fraud claims. Results reveal that the tree augmented NB outperformed other models based on several performance metrics with accuracy (79.35%), sensitivity (44.70%), misclassification rate (20.65%), area under curve (0.81) and Gini (0.62). In addition, the result shows that the AdaBoost algorithm can improve the classification performance of the decision tree. These findings are useful for insurance professionals to identify potential insurance fraud claim cases

Oil prices and Malaysian economy

This paper studies the impact of oil prices on GDP in Malaysia. In particular, three types of oil prices; world oil price (PW), world oil price in domestic currency (PWD), and domestic oil price (PD) are tested against the GDP within VAR framework. Based on the findings, change in PD oil price appears to have the most pronounced effect to the GDP. It is because, significant results of PD analysis are documented both in short-run and long-run tests. In the asymmetric test, significant result is documented in PD analysis only. The finding signifies the presence of asymmetric relationship between oil price changes and the economy. With these evidences we conclude that, policymakers may consider using PD oil price as a policy tool in the case oil price increase strikes again in the future. In the event policymakers are faced with policy options of either to increase or decrease the oil price, they should be aware that oil price decrease gives significant effect to the economy than oil price increase

Oil price exposure to asset returns: a disaggregate analysis

The paper analyzed oil price exposure on asset returns of eight economic sectors namely- Construction (CON), Consumer (CSU), Finance (FIN), Industrial (IND), Plantation (PLN), Property (PRP), Services (SER), and Mining (TIN). of economy. Two tests, identified as Model 1 and Model 2, were conducted via the Augmented-CAPM (A-CAPM) approach. The first was a symmetric analysis while the second was an asymmetric typed of analysis. The estimated results from Model 1 documented insignificant results in all sector analyses. These findings signified that the stock returns were not exposed to oil price shocks. The estimated results of Model 2 indicated the presence of significant finding in industrial (IND) sector, of the PW analysis. The returns of the IND sector were negatively exposed to change in PW oil price, and it was more significant during periods of oil price increased. In other word, the event of oil price increased significantly reduced the returns of the IND sector