Single Equation Model Research Articles

Panel data modeling: Identifying and handling outliers with the VSOM approach

While modeling panel data, identifying outliers is crucial, yet visually spotting them can be challenging. However, not many methods exist for outlier detection in panel data models other than robust estimation methods. This study uses the variance shift outlier model (VSOM) approach to identify and handle outliers in panel data modeling, both in single and simultaneous equation modeling. This study applies the VSOM approach to GDP and FDI data from ten countries that are part of the ASEANChina Free Trade Area (ACFTA). The results demonstrate that the VSOM approach effectively handle outliers in panel data modeling, in both single and simultaneous equation model. Specifically, the VSOM model shows a lower sum of squared residuals (SSR) compared to the null model. This indicates that VSOM successfully reduces the impact of outliers, leading to improved model fit and accuracy in capturing the underlying relationships within the data. Some of the highlights of the proposed approach are:•Identifying the square of the standardized residual.•Generate the distribution of the squared standardized residuals by parametric bootstrapping.•Reducing the impact of observations identified as outliers by downweighting their variance through the addition of a D matrix.

How much financing China needs to achieve carbon peak and carbon neutrality goals?

China requires financial support to achieve its dual‑carbon goals, the carbon emission peak and neutrality. However, currently, there lack of systematic estimation of the amount and structure of finance needed to achieve these goals. This paper attempts to fill the research gap by constructing a simultaneous equations model that characterizes the five core channels that finance contributes to carbon emission. Cointegration estimation, suitable for long-term forecasting, was used to estimate the amount of finance required for carbon emission paths planned by the International Energy Agency (2021) for China to achieve dual‑carbon goals. Finally, the finance structure was estimated using the Bootstrap method. We found that first, estimations of the simultaneous equations model perform better than the existing single equation models. Second, finance influences carbon emissions through economic development, employment (industry) structure, foreign direct investment, energy structure, and energy technology. There are long-run equilibrium relations between these variables. Third, the financing required for the dual‑carbon goals will increase from 2021 and grow at a relatively stable rate higher than history. The earlier carbon neutrality, the more financing is needed. Financing expansion to achieve the emissions peak before 2030 is small, but achieving carbon neutrality before 2060 is challenging. Fourth, the finance structures ranked by their shares in the total amount are indirect financing, other financings, direct financing, and shadow banking. The future paths of these financings have different fluctuation patterns due to their varied embedded risks.

Parametric Stochastic Frontier Approach To Measure Efficiency Pre-And-Post-Merger Bank Syariah Indonesia

This research analyses the efficiency of pre-and-post-merger Bank Syariah Indonesia (BSI). This research used a descriptive quantitative analysis method. The population in this research is Islamic banks, which were merged into BSI. The sampling technique was carried out using saturated samples, resulting in the merged of three Islamic Banks, namely Bank Syariah Mandiri (BSM), Bank Negara Indonesia Syariah (BNIS), Bank Rakyat Indonesia Syariah (BRIS), to become BSI. The data used is secondary data in the form of quarterly financial reports for 2019-2022. The research focused on input variables such as total fixed assets, third-party funds, operating costs, and financing. The data analysis techniques used to measure the efficiency of Islamic banks are the Econometric Model (Single Equation Model), Stochastic Frontier Analysis (SFA), and Independent Sample t-test. The result showed that pre-merger, the total fixed asset, total third-party funds, and operating cost as the input variables of the three Islamic Banks were optimal for generating financing. Therefore, the total assets, total third-party funds, and operating costs produced a more optimal impact on the distribution of total financing. It is shown that BSI, both pre-and-post-merger, has generally been efficient in its operational activities. The results of this research complement the theory related to the efficiency level of Islamic banks in terms of the amount of financing as measured by fixed assets, total third-party funds, and operational costs. Practically, the results of this research can be a reference for banks, especially Islamic banks, that will carry out mergers to measure their efficiency level.

Design and Pricing Analysis of Electricity Retail Package System Based on Single Pendulum Equation

The electricity retail industry is becoming increasingly competitive, and retailers are looking for innovative ways to attract and retain customers. One potential strategy is to offer retail packages that include electricity pricing based on the single pendulum equation (SPE). This article discusses the design of a retail package system for electricity retailers based on the SPE. The system utilizes real-time data on electricity supply and demand to create a dynamic pricing system that adjusts prices based on changes in the market. This article present the single pendulum equation model and data obtained from Residential Electricity End-use Demand Dataset of Costa Rica (REEDD-CR). It outlines the key steps in designing the system, including gathering data on electricity supply and demand patterns, creating a pricing algorithm based on the single pendulum equation, and integrating the system with billing and customer management systems. The article also emphasizes the importance of considering customer preferences and behavior in the design of the system. The study findings stated that single pendulum model has provided an evaluation time of 1.5s and price and demand value of 0.6. A well-designed dynamic pricing system based on the single pendulum equation has the potential to provide customers with cost savings and increased flexibility while allowing retailers to optimize their pricing strategies in a competitive market.

FACTORS INFLUENCING ONLINE SHOPPING BEHAVIOUR OF YOUTH CUSTOMERS IN MALAYSIA AFTER COVID-19 PANDEMIC

Background and Purpose: The Movement Control Order (MCO) requires a higher demand for online services. In light of recent events in the business environment, it is becoming challenging to ignore online channels, including online shopping platforms. The current study investigates the impact of customer satisfaction, convenience, social media influence, and website on online shopping behaviour.
 
 Methodology: Two hundred respondents were selected based on the convenience sample. Online questionnaires were distributed to young Kota Kinabalu, Sabah, Malaysia customers. This case study was conducted after the Covid-19 pandemic in Kota Kinabalu, Sabah. Harman's Single Factor Test, Validity test, and Partial Least Square Structural Equation Model were used to validate the model of this study and the relationship between constructs.
 
 Findings: The results reveal that customer satisfaction, convenience, and social media influence are significantly related to the online shopping behaviour of youth in Malaysia after Covid-19 pandemic. Furthermore, the relationship between customer satisfaction and online shopping behaviour is higher than that between other factors in this study model.
 Contributions: In theory, this study contributes to understanding Malaysian youth customers' online shopping behaviour. Businesses must take full advantage of e-commerce platforms to ensure customer satisfaction and build customer trust through online shopping services.
 
 Keywords: Convenience, customer satisfaction, online shopping behaviour, youth customers, social media influence.
 
 Cite as: Rahlin, N. A., Jas, O., Fauzi, S. N. M., & Bahkia, A. S. S. A. (2024). Factors influencing online shopping behaviour of youth customers in Malaysia after Covid-19 pandemic. Journal of Nusantara Studies, 9(1), 193-223. http://dx.doi.org/10.24200/jonus.vol9iss1pp193-223

Association of copayments with healthcare utilization and expenditures among Medicaid enrollees with a substance use disorder

BackgroundThe purpose of this study was to examine the association between copayments and healthcare utilization and expenditures among Medicaid enrollees with substance use disorders. MethodsThis study used claims data (2020−2021) from a private insurer participating in Arkansas's Medicaid expansion. We compared service utilization and expenditures for enrollees in different Medicaid program structures with varying copayments. Enrollees with incomes above 100 % FPL (N = 10,240) had copayments for substance use treatment services while enrollees below 100 % FPL (N = 2478) did not. Demographic, diagnostic, utilization, and cost information came from claims and enrollment information. The study identified substance use and clinical comorbidities using claims from July through December 2020 and evaluated utilization and costs in 2021. Generalized linear models (GLM) estimated outcomes using single equation and two-part modeling. A gamma distribution and log link were used to model expenditures, and negative binomial models were used to model utilization. A falsification test comparing behavioral health telemedicine utilization, which had no cost sharing in either group, assessed whether differences in the groups may be responsible for observed findings. ResultsSubstance use enrollees with copayments were less likely to have a substance use or behavioral health outpatient (−0.04 PP adjusted; p = 0.001) or inpatient visit (−0.04 PP; p = 0.001) relative to their counterparts without copayments, equal to a 17 % reduction in substance use or behavioral health outpatient services and a nearly 50 % reduction in inpatient visits. The reduced utilization among enrollees with a copayment was associated with a significant reduction in total expenses ($954; p = 0.001) and expenses related to substance use or behavioral health services ($532; p = 0.001). For enrollees with at least one behavioral health visit, there were no differences in outpatient or inpatient utilization or expenditures between enrollees with and without copayments. Copayments had no association with non-behavioral health or telemedicine services where neither group had cost sharing. ConclusionCopayments serve as an initial barrier to substance use treatment, but are not associated with the amount of healthcare utilization conditional on using services. Policy makers and insurers should consider the role of copayments for treatment services among enrollees with substance use disorders in Medicaid programs.

Regression Analysis: A Theoretical Approach

Abstract The main objective of this document is to provide a comprehensive understanding in the area of simple regression, especially for undergraduate students majoring in economics, finance and statistics. JEL classification numbers: C01, C013, C51, C52. Keywords: Econometrics, single equation model, Estimation.

BLACK MALES IN NON-STEM AND STEM OCCUPATIONS

While many labor market studies have examined wage inequality by race, gender, and class, the research has seldom directly considered labor market outcomes of STEM college graduates within the context of non-STEM and STEM occupations. The current study investigates the determinants of wages among Black males in STEM and non-STEM occupations compared to their White male peers. Through this investigation, it explores the feasibility of broadening Black males' participation in STEM occupations but also how they might earn higher wages and thereby close the wage gap with White male peers. The Public Use Microdata Sample (PUMS) files for the 2018 American Community Survey (ACS) were the primary data source for the current study. Following the convention in labor economics, the author used Mincer's single-equation model to explain variations in earnings as a function of select wage determinants derived from the data. Three main insights emerged from the current study. The findings suggested that opportunities do exist for employers to hire qualified Black males seeking gainful employment in STEM occupations. The findings also indicated that within the Black male group, working in a STEM occupation with a college degree in a STEM field was the best route to attain maximum wages. The third insight from the current study cannot be avoided: the noticeable gaps in wages between White and Black males. Implications of the findings for employers seeking to diversify their STEM workforce and for Black males considering employment or employed in a STEM occupation are discussed.

Impact of Foreign Direct Investment on Economic Growth

Foreign direct investment (FDI) is a force of economic growth. FDI fills the gap between demand for capital and supply of capital that rise the productive investment and economic growth within the country. This paper aims to investigate the impact of FDI on economic growth of the country. Engel-Granger cointegration test is used by employing the time series data of 1995/96—2021/22 and error correction model. Neo-classical growth model is the main basis single equation model whereas real FDI is explanatory variable and GDP is the proxy for economic growth. Cointegration results confirms FDI makes the positive impact on economic growth in short-run as well as in long-run. The error correction term (0.67) indicates the disequilibria of GDP move towards the equilibrium at the speed of 65% in successive year. Therefore, this paper concludes to raise the FDI flows within the country. The Government should make the favorable environment — control money supply, direct remittance towards productive sector—for foreign investors which leads to rise economic growth within the country.

Voluntary sustainability standards and farmer welfare: The pathways to success?

Whether Voluntary Sustainability Standards (VSS) - such as Fairtrade, GlobalGAP or Organic - may contribute to economic sustainability has been subject to vigorous debate over the past decades. To analyze the welfare effects of VSS for family farms, previous studies rely on single equation models which enable analyzing if (some) VSS affect welfare, but not how (some) VSS affect welfare – or not. Hence, little is known about the mechanisms and the relative importance of these different mechanisms by which VSS contribute to farmer welfare. In this paper, we analyze the channel of effects through which VSS affect net farm revenue, as a proxy of farmer welfare, of family farms in Peru. We use nationwide data from Peru’s National Agricultural Survey covering five years, multiple agricultural commodities, and multiple VSS. We apply a multiple mediation model which allows to disentangle the main revenue-determining mechanisms and to compare their relative importance. We find that prices (and not yields) are the main channel through which VSS affect net farm revenue. However, higher prices cannot offset higher production costs, resulting in zero net revenue gains. We do not find an effect through yields, but identify a large potential effect on net farm revenue. We find heterogeneity in the effects by standard and crop, with crops certified to standards that apply a system of quality-based price differentiation having the largest impact on net farm revenue through a price effect. From a policy perspective, we highlight potential improvements in VSS design to effectively improve economic sustainability.

On the Dynamic Relationship between Household Debt and Income Inequality in South Africa

This paper analyses the relationship between household debt and income inequality in South Africa for the period 1980–2021. We use two measures of inequality and estimate a vector error correction model (VECM) which includes household debt, inequality, and other macroeconomic variables. To test the robustness of our results, single equation models are used, which estimate household debt as a function of inequality and macroeconomic factors. We employ two measures of inequality, namely Gini coefficient and ratio of top and bottom income earners’ proportion of income. Furthermore, we use both household debt as a percentage of disposable income and household debt service costs as dependent variables in single equation regressions. The study finds a negative and significant relationship between household debt and income inequality in the long run, which contradicts the Rajan hypothesis in the South African case. Rather, we find that inequality in South Africa creates a bias in debt allocation towards high-income earners, whose incomes can easily absorb the extra debt (reduced ratio of debt to disposable income). There are therefore no socio-equity considerations in South African credit markets. We find growth in gross domestic product (GDP) per capita also has a moderating effect on the relationship between household debt and income inequality. High GDP per capita growth in the presence of high inequality reduces the impact of inequality on household debt and vice-versa. All other control variables take expected signs. These results are robust to changes in the inequality or household debt measures.

The pattern of healthy diets and zero hunger among households in South-West Nigeria: application of linear approximation to quadratic almost ideal demand system.

Malnutrition and food insecurity remain a significant public health challenge globally, affecting millions of people, particularly in low- and middle-income countries. In Nigeria, the prevalence of malnutrition and food insecurity is high, with a significant burden in the South-West region. Despite several interventions aimed at promoting healthy diets and reducing food insecurity, little is known about the pattern of healthy diets and zero hunger among households, as well as the budget shares on the food items driving these outcomes. Therefore, this study analyzes the pattern of healthy diets and zero hunger among households in South-West Nigeria, using the primary data elicited from 600 rice-consuming households, drawn through a multistage random sampling technique. Descriptive statistics and Linear Approximation to Quadratic Almost Ideal Demand System (LA-QUAIDS) model were used to analyze the dataset. The estimated LA-QUAIDS model was helpful to decipher the relationships that may not be possible to discover using a single-equation model. The finding of this study revealed that rice, especially local (Ofada) rice, is the most consumed food item among the households in the study area with a monthly budget share of 0.195. This is an indication that households spend approximately 19.5% of their monthly food expenditure share on rice consumption. The results also indicated that yam flour (-0.10), cassava-gari (-2.12), and meat (-0.03) are net complements to rice, while the rest of the food items are regarded as net substitutes. The estimated compensated (-1.64) and uncompensated (-1.69) own-price elasticities of local rice, respectively, indicate that local rice variety is price inelastic, and the estimated expenditure elasticity (0.02) suggests that local rice is not a luxury food in the household food basket but a necessity. This study affirms the importance of locally produced foods, especially local rice to the households in the study area. In light of the findings, this study recommends adequate policy aimed at reducing the cost of local food production by boosting domestic production. Apparently, this will technically trigger market price adjustment, as shown in this study, where local rice was estimated to be own-price elastic in nature.

Impact of energy policies on residential low-carbon behaviors by considering Place attachment: Evidence from China

Human activities are the primary source of energy consumption and CO2 emissions. Adopting low-carbon behaviors (LCBs) can effectively reduce carbon emissions, which in turn helps alleviate environmental problems. Previous research shows that low-carbon policies can promote LCBs, while an extensive understanding of the effects of multi-types of low-carbon policies on various LCBs needs to be verified. Analyses on influencing factors regarding LCBs are dominated before, and place attachment and low-carbon behavioral intention as the influencing factors of LCBs, their relationship with low-carbon policy and LCBs needs to be clarified. By taking a questionnaire survey of residents of Hangzhou, China, this study presents a conceptual framework capable of analyzing the relationship between three types of low-carbon policies, including information policy, economic policy, and administrative regulations, and two types of LCBs, including low-carbon consumption (LCCB) and travel (LCTB) behavior, considering the mediation effect of place attachment and low-carbon behavioral intention in a single structural equation model. The results illustrate that administrative regulations and information policy have a direct positive impact on LCCB, and information policy has the most significant influence. Economic policy and administrative regulations directly impact LCTB, and administrative regulations have the most significant influence. The influence of administrative regulations on LCTB is more excellent than on LCCB. Information policy indirectly affects two types of LCBs through the chain mediation effect of place attachment and low-carbon behavioral intention. The results should be helpful to low-carbon policymakers seeking to promote LCBs to consider the importance of place attachment and various low-carbon policies. Moreover, they enrich our understanding of the influencing mechanism of LCBs.

Ultrafast Mechanism of Material Removal in the Femtosecond Laser Ablation of WS2 and Its Diode Rectification Characteristics

The study investigates the two different underlying ablation mechanisms of WS2 processed by femtosecond (fs) laser with different fluences. With increasing fluence, the saturable expansion of craters and the transformation of three distinct crater morphologies are found. The material response and the transfer and deposition of laser energy are tracked by using a plasma model based on the classical single rate equation model and the Drude model. The results of the numerical simulation and time-resolved transient reflectivity reveal the two different ablation mechanisms, which are coulomb explosion and phase explosion. The mechanism of material removal is distinguished by the critical threshold of 0.85 J/cm2. In addition, the internal ablation region exhibits a high concentration of defects and WO3 according to the results of Raman spectra, X-ray photoelectron spectra, and morphology-dependent photoluminescence mapping. Due to the high concentration with high fluence, the device of WS2/Si p-n junction exhibits a 2.6 times enhancement on the current under forward bias. The findings would be of value to engineer structures to tailor the optoelectronic response of WS2 and to develop potential future optoelectronic devices.

The impact of perceived safety, weather condition and convenience on motorcycle helmet use: The mediating role of traffic law enforcement and road safety education

Despite numerous studies on motorcycle safety, especially the compliance of helmet use laws in both developed and developing countries across the globe, little is known about the mediating role of traffic law enforcement and road safety education specifically on the relationship between helmet use influencing factors and helmet usage in general. The aim of this study was to examine the mediating role of traffic law enforcement and road safety education on the relationship between helmet usage influencing factors and motorcycle helmet usage. A total of 358 respondents from a university community that uses a motorcycle on daily bases to and from the community and for other important trip purposes completed a self-reported questionnaire in the Upper West Region of Ghana where motorcycles are predominantly used as a transportation mode. To test for the various hypotheses of this study, we developed a hypothesized single multiple mediated structural equation model and several sub-mediated models using AMOS 26.0. The results showed that the perceived safety of the helmet, weather conditions, and convenience of helmet use have positive significant impacts on helmet use. The study also found a full mediation role of the combined effect of traffic law enforcement and road safety education on the relationship of helmet use influencing factors investigated and helmet use. The study concludes that new traffic law enforcement and road safety education strategies need to be adopted to help improve upon the low prevalence of helmet use within the study area.

Cue consistency matters: how and when newcomers respond to supervisor creativity expectations

Organizations may hire newcomers as a source of creativity, bringing fresh ideas and novel solutions to benefit organizational performance. However, the conditions that foster newcomer innovation are not well understood. Drawing on behavioral plasticity and cue consistency theories, we investigate the combined influence of new job self-efficacy and two work design factors (work autonomy and work demands) affecting how supervisor creativity expectations (SCEs) translate into newcomers behaving innovatively. Two-wave data were collected from 108 graduates of a university in China. Results using reliability-corrected single indicator latent moderated structural equation modeling (RCSLMS) supported our hypotheses. Thus, SCEs predicted newcomer innovative behavior more strongly for newcomers with low new job self-efficacy. Moreover, supporting cue consistency theory, newcomers who perceived high SCEs and low new job self-efficacy demonstrated the highest level of innovative behavior when work autonomy was high or work demands were low. These results broaden the application of behavioral plasticity theory for understanding newcomer behaviors. Further, our findings emphasize the importance of consistent work environment cues to encourage newcomer innovation.

Estimating the size of informal economy in a post-transition country – the case of Poland

ABSTRACT The size of the informal economy in Poland is estimated by means of the Currency Demand Approach (CDA). Using quarterly data for the period 1999–2019, we adopt two separate econometric approaches. First, we specify a single equation model to estimate it with the Fully-Modified OLS method. Second, the CDA coefficients are treated as a cointegrating vector in a cointegrated VAR. The size of the informal economy in Poland is found to have diminished from about 32% of GDP in 2000 to about 12% of GDP in 2019. We provide confidence intervals for our estimates which, to our best knowledge, are rarely presented in the literature; their width ranges from 3 to 7% of GDP.

Two-parameters single equation stem taper models of Pinus sibirica in Siberia, Russia

A large number of studies have been devoted to the cedar forests in Russia, but studies of the conicity of trunks remain limited. The main goal of this study was to analyze two-parameter single equation stem tapper models for Siberian cedar trees, which will serve as guidelines for future research. The study tested six two-parameter models of one equation for the conicity of the trunk of Siberian cedar trees. For this, data from 1805 measurements of diameters in 193 felled trees were used. The data were collected in natural pure and mixed Siberian pine stands in Irkutsk region (Southern Siberia) and Tyumen region (Western Siberia), Russia. Our analysis showed that for our data set, the Reed and Green model turned out to be the best model. The model is characterized by the smallest average absolute error percentage, the square root of the root mean square error, and the largest coefficient of determination. The residuals of this model are independent and characterized by constant variance. The analysis performed showed that two-parameter single equation models have a good fit in the central part of the trunk, therefore, forestry management in cedar forests should be used with caution. For the purposes of forestry management in cedar forests, it is recommended to develop and put into practice more complex models.

Profile likelihood-based parameter and predictive interval analysis guides model choice for ecological population dynamics

Calibrating mathematical models to describe ecological data provides important insight via parameter estimation that is not possible from analysing data alone. When we undertake a mathematical modelling study of ecological or biological data, we must deal with the trade-off between data availability and model complexity. Dealing with the nexus between data availability and model complexity is an ongoing challenge in mathematical modelling, particularly in mathematical biology and mathematical ecology where data collection is often not standardised, and more broad questions about model selection remain relatively open. Therefore, choosing an appropriate model almost always requires case-by-case consideration. In this work we present a straightforward approach to quantitatively explore this trade-off using a case study exploring mathematical models of coral reef regrowth after some ecological disturbance, such as damage caused by a tropical cyclone. In particular, we compare a simple single species ordinary differential equation (ODE) model approach with a more complicated two-species coupled ODE model. Univariate profile likelihood analysis suggests that the both models are practically identifiable. To provide additional insight we construct and compare approximate prediction intervals using a new parameter-wise prediction approximation, confirming both the simple and complex models perform similarly with regard to making predictions. Our approximate parameter-wise prediction interval analysis provides explicit information about how each parameter affects the predictions of each model. Comparing our approximate prediction intervals with a more rigorous and computationally expensive evaluation of the full likelihood shows that the new approximations are reasonable in this case. All algorithms and software to support this work are freely available as jupyter notebooks on GitHub so that they can be adapted to deal with any other ODE-based models.

Exploring Poverty-tourism Nexus in South Asian Countries: A Panel Dynamic Estimation

Using the time series from World Bank (1995–2019), the present article explores the relationship between tourism inflow and poverty alleviation (per capita household consumption) within the South Asian Association for Regional Cooperation (SAARC) region. The article employs three alternative approaches of PARDL, namely pooled mean group (PMG), mean group (MG) and dynamic fixed effects (DFE) estimators. In addition, two substitute single-equation models, namely dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS), are employed to estimate the long-run relationship between poverty alleviation, tourism inflow and other control variables. The results suggest that tourism inflow met the a priori expectation—positively influencing poverty alleviation within SAARC countries in the long run. Furthermore, poverty is reduced by increasing per capita income and output in the industry sector. Poverty can worsen due to an increase in the total trade of member countries. In addition, the findings indicate the insignificant impact of the agricultural sector on poverty alleviation and the unanimous effect of the service sector on poverty. Based on these findings present article frames various policy implications.