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This study aims to examine the effects of participating in physical activities on female college graduates' starting salaries. We used an instrumental variable (IV) approach to address the possible endogeneity problem. By using the Taiwan Higher Education Dataset, we discovered that participating in physical activities during college increased an individual's earnings by 3.06%. The significant positive effect of physical activity on salary demonstrated in this study is consistent with that in other relevant studies. This study also discovered that both the intensity and the persistence of participation in physical activities affected salary outcomes. Individuals earned 0.17%–2.41% more if they exercised for an additional hour per week, suggesting the importance of the intensity of participation in physical activities. In addition, persistent participation in physical activities was associated with a 3.08% higher salary.

The COVID-19 pandemic has wrought havoc on economies around the world. The purpose of this study is to learn about the distributional impacts of the pandemic.

The authors contribute new theoretical and empirical evidence on the distributional impacts of the pandemic on different income groups in a multicountry setting. The authors analyze rich individual-level survey data covering 6,082 respondents from China, Italy, Japan, South Korea, the United Kingdom and the United States. The results are robust to various econometric models, including ordinary least squares (OLS), Tobit and ordered probit models with country-fixed effects.

The authors find that while the outbreak has no impact on household income losses, it results in a 63% reduction in the expected own labor income for the second-poorest income quintile. The pandemic impacts are most noticeable for savings, with all the four poorer income quintiles suffering reduced savings ranging between 5 and 7% compared to the richest income quintile. The poor are also less likely to change their behaviors regarding immediate prevention measures against COVID-19 and healthy activities. The authors also found countries to exhibit heterogeneous impacts.

Designing tailor-made social protection and health policies to support the poorer income groups in richer and poorer countries can generate multiple positive impacts that help minimize the negative and inequality-enhancing pandemic consequences. These findings are relevant not only for COVID-19 but also for future pandemics.

The authors theoretically and empirically investigate the impacts of the pandemic on poorer income groups, while previous studies mostly offer empirical analyses and focus on other sociodemographic factors. The authors offer a new multicountry analysis of several prevention measures against COVID-19 and specific health activities.

This study aims to examine the premature deindustrialization risk in Vietnam.

This study uses a manufacturing–income relationship to conduct an empirical estimation. The latecomer index is adopted in the regression model to identify a downward shift of latecomer's relationship.

The empirical analysis indicates that there is a risk of premature deindustrialization in the Northern Midlands and Mountain Areas. The provinces with low trade openness or foreign direct investment may experience risk of premature deindustrialization.

This study proposes technology diffusion as a policy direction to prevent premature deindustrialization. Furthermore, the Vietnamese government should improve the business environment in the Northern Midlands and Mountain Areas by promoting and attracting export-oriented foreign direct investment.

This study is the first to examine premature deindustrialization in Vietnam based on provincial-level data.

The paper is concerned with exploration of sensor signals in differential electronic nose. It is a special type of nose, which applies double sensor matrices and exploits only their differential signals, which are used in recognition of patterns associated with them. The purpose of this paper is to study the application of differential nose in dynamic measurement of aroma of 11 brands of cigarettes.

The most important task in pattern recognition using electronic nose is its resistance to the noise corrupting the measurement. The authors will analyze and compare the performance of the nose in the noisy environment by applying two classifier systems: the support vector machine (SVM) and random forest (RF) of decision trees.

On the basis of numerical experiments the authors have found that application of SVM as the classifier in the electronic nose is more advantageous than RF, especially at high level of noise and small number of measuring sensors. Its application allowed to recognize 11 brands of cigarettes with the accuracy close to 100 percent.

Thanks to application of two identical sensors working in a differential mode the authors avoid the baseline estimation and thus the solution is well suited for on-line dynamic measurements of the process.

The paper has studied the advantages and limitations of the differential electronic nose following from the existence of the noise, corrupting the measurements. It has pointed an important role of the applied classifier system in getting the electronic nose of the highest quality.

The main aim of this study was to examine gender differences in job satisfaction in Europe.

For the empirical analysis, data from the Sixth European Working Conditions Survey were used. Oaxaca–Blinder decomposition with a principal component analysis (PCA) aggregated variable, after unconditional quantile regressions in a multiple imputation background, was implemented.

Women report higher job satisfaction than men do. Women were significantly more satisfied than men for the middle levels of the job satisfaction distribution.

This study expands the evidence on the determinants of job satisfaction in the European labour market by applying a recent form of decomposition that invests in unconditional quantile regression (UQR). To the best of this study knowledge, this is the first time that the Oaxaca–Blinder decomposition with a PCA aggregated variable after unconditional quantile regression has been employed to study gender-based differences in job satisfaction.

This analysis examines the relationship between corruption and firm productivity in Vietnam.

The authors apply the system generalized method of moments estimation approach on a panel dataset constructed from comprehensive enterprise surveys covering all the sectors over the 2011–2020 period.

The results confirm a non-linear relationship between corruption and firm productivity. Where corruption is severe, leaving corruption alone tends to benefit firm productivity because efforts to control corruption are likely to cause greater delays. In less corrupt provinces, corruption appears to harm firm productivity while efforts to control corruption provide significant productivity gains. This U-shaped relationship is confirmed for small firms and those in the private sector sub-samples. Intriguingly, this study reveals that the U-shaped relationship does not apply to micro, medium, large firms, state-owned firms and foreign-invested firms because corruption is found to have no significant impact on productivity among these sub-samples. Changes in regulations after 2014 toward promoting a transparent business environment are shown to foster the positive impact of lowering corruption on firm productivity.

This study suggests that lowering corruption is beneficial for firm productivity at the micro level. However, where corruption is severe, monitoring corruption alone is likely to cause adverse effects on productivity due to increased bureaucratic delays. Institutional reforms might play an important role in leveraging the effects of lowering corruption on productivity in highly corrupt areas.

This paper sheds new light on the relationship between corruption and firm productivity in the broad existing literature and especially in the limited number of studies for Vietnam.

This study aims to address two research questions. First, do the agricultural extension services have an impact on the potential outcomes considered in the primary studies, and to what extent? Second, how sensitive is the reported impact to the study-specific characteristics in the primary studies?

The paper synthesizes 45 studies that assessed the causal impact of agricultural extension services published in 2004–2021, using meta-regression analysis. It considers three measures of effect sizes – Cohen’s, Hedges and principal correlation coefficient (PCC) – to standardize the reported impact of agricultural extension services in the primary studies.

The empirical results show that, on average, agricultural extension services have statistically significant and positive impacts on the potential outcomes identified in the primary studies. However, the magnitude of the impact is considered medium-sized. Other results show that the effect size estimates of agricultural extension services' impact significantly vary with the data type (cross-sectional data vs. panel data), research design (non-experimental vs. experimental design) and econometric methods employed in the primary studies.

One can argue that the medium-sized impact we estimated indicates evidence of a moderate, weak relationship between agricultural extension services and the potential outcomes considered in the primary studies. This means that agricultural extension services need to be restructured in the current form to stimulate change in the agricultural sector globally. In addition, the sensitivity of effect sizes to study attributes (i.e. data types, research design and econometric methods) shows that researchers and academicians need to pay attention to these attributes to provide more reliable estimates for policy purposes.

This is the first study that attempts to shed light on the overall performance of agricultural extension services using a meta-regression analysis approach.

Looks at the problems and methods of providing companies with detailed information about their own sales and marketing costs. Shows how a database can be constructed using the concept of marketing cost analysis. Describes profitability analysis for customers, products and any market segment required. Discusses potential problems with accuracy and the marginal cost approach, going on to show how the database should be expanded to form a complete marketing information system.

‘In some traditional craft apprenticeships there is a need to remove age restrictions and to place much greater weight on the attainment of recognised standards of performance. Tests of trainee performance after particular phases of training are already applied in certain schemes but we need to build on such developments and make them more general.’ So said the Secretary of State for Employment Jim Prior in the House of Commons recently. And his views are being echoed throughout Industry with more and more people agreeing that there is a need to train to measurable standards of skill. In fact the RTITB Skills Assessment programmes are specifically designed with this in mind and have been steadily developed since they were launched in 1975, following two years of closely controlled pilot tests.