Slope Coefficient Research Articles

Liquid Chromatographic-Electron Spray Ionization-Mass Spectroscopy Technique for the Simultaneous Determination of Ethinyl Estradiol & Etonogestrel and Characterization of New Forced Degradation Compounds

The aim of the current study was to develop, validate a precise, rapid, accurate liquid chromatography-mass spectrometry (LC-MS) method for the simultaneous estimation of ethinyl estradiol and etonogestrel. The retention times of ethinyl estradiol and etonogestrel were found at 3.112 min and 4.399 min, respectively, whereas the linear range were found in the concentration ranges from 0.04-0.23 µg/mL & 3-18 µg/mL with slope coefficient (R2) of 0.9992 and 0.9991 correspondingly. Similarly, the accuracy values for ethinyl estradiol and etonogestrel were found to be 100.5% and 100.1% correspondingly. As per ICH Q2(R1) guidelines, the method was validated with liquid chromatography-mass spectrometry to confirm the newly obtained degradation compounds chemical structures of ethinyl estradiol and etonogestrel.

Evapotranspiration Partitioning and Estimation Based on Crop Coefficients of Winter Wheat Cropland in the Guanzhong Plain, China

Accurate estimation and effective portioning of actual evapotranspiration (ETa) into soil evaporation (E) and plant transpiration (T) are important for increasing water use efficiency (WUE) and optimizing irrigation schedules in croplands. In this study, E/T partitioning was performed on ETa rates measured using the eddy covariance (EC) technique in three winter wheat growing seasons from October 2020 to June 2023. The variation in the crop coefficients (Kc, α, and KHc) were quantified by combining the ETa and reference evapotranspiration rates using the Penman–Monteith, Priestley–Taylor, and Hargreaves equations. In addition, the application of models based on the modified crop coefficient (Kc, α, and KHc) was proposed to estimate the ETa rates. According to the obtained results, the average cumulative ETa, T, and E rates in the three winter wheat growth seasons were 471.4, 265.2, and 206.3 mm, respectively. The average T/ETa ratio ranged from 0.16 to 0.72 at the different winter wheat growth stages. Vapor pressure deficit (VPD) affected the ETa rates at a threshold of 1.27 KPa. The average Kc, α, and KHc values in the middle stage were 1.34, 1.54, and 1.21, respectively. The measured ETa rates and ETa rates estimated using the adjusted Kc, α, and KHc showed regression slope coefficients of 0.96, 0.99, and 0.96, and coefficients of determination (R2) of 0.92, 0.93, and 0.90, respectively. Therefore, the Priestley–Taylor-equation-based adjusted crop coefficient is recommended. The adjusted crop-coefficient-based models can be used as valuable tools for local policymakers to effectively improve water use.

Regional outcome disparities in German head and neck cancer patients: Shorter survival in Eastern Germany.

Demographics are important prognostic factors in malignant diseases. A nationwide analysis concerning the prognostic impact of demographics in head and neck cancer (HNC) patients (HNCP) has not been performed previously. A retrospective analysis of data from the Center for Cancer Registry Data (ZfKD) and the Federal Statistical Office (Destatis) between 2002 and 2017 was performed. A total of 212'920 HNCP were included. Incidence, tumor stage, age development, sex distribution, age-, residence-, and diagnosis-time-specific survival were examined. Mean age of HNCP increased more rapidly than in the general population (slope coefficient: 0.29 vs. 0.20; p < 0.0001). Higher age and male sex were associated with a worse prognosis. Whereas overall survival (OS) increased from the early to the later observation period for HNCP <70 years, no OS improvement for HNCP >70 years was found. Furthermore, an OS disadvantage was observed for East Germany compared to West Germany (median 47 vs. 60 months; p < 0.0001). This disparity was associated with a disproportionately high ratio of men in East Germany (men/women: 4.4 vs. 3.1; p < 0.0001) and a lower mean age (61 vs. 63 years; p < 0.0001). In addition to stage, age and sex, residence in East Germany were confirmed as an independent factor for OS in a multivariate analysis. Finally, three decades after the German reunion, a survival disadvantage for patients in East Germany still exists. This discrepancy may be a result of socioeconomic disparities.

Monetary shocks and production network in the G7 countries

Understanding the structure and properties of production networks is essential to identify the transmission channels from monetary shocks. While growingly studied, this literature keeps displaying critical caveats from which the investigation of G-7 economies is not spared. To fill this gap, this paper applies a version of Time-Varying Parameters Bayesian Vector-Autoregressions models (TVP-VAR) and investigates the responses of production networks (upstream and downstream dynamics) to endogeneous monetary shocks on key macro-level indicators (GDP, GDP deflator, exchange rate, short-term and long-term interest rates). Two distinct time-lengths are considered: a test (i.e., 2000–2014) and a treated period (i.e., 2007–2009,”the Great Recession”). Prior, key statistical conditions are checked using a stepwise stationary testing framework including the Kwiatkowski–Phillips–Schmidt–Shin (Kapetanios et al. in J Economet 112(2):359–379, 2003—KPSS) and panel Breitung (Nonstationary panels, panel cointegration, and dynamic panels. Emerald Group Publishing Limited, London, 2001) unit root tests; followed by the Pesaran (General diagnostic tests for cross section dependence in panels, 2004) Cross-sectional Dependence (CD) test; and the Im–Pesaran–Shin (Im et al. in J Economet 115(1):53–74, 2003—IPS) test for unit root in the presence of heterogenous slope coefficients. Panel Auto-Regressive Distributed Lag Mean Group estimates (PARDL-MG) offer interesting short- and long-run monetary shocks-production networks response functions, stratified by country and sector. Findings clearly indicate that upstreamness forces dominated downstremness dynamics during the period 2000–2014, whereas the financial sector ermeges as the clear transmission channel through which monetary shocks affected the productive economy during the Great Recession. In general, we conclude that the prioduction structure influences the transmission of monetary shocks in the G-7 economies. Adequate policy implications are supplied, along with a methodological note on the forecasting potential of TVP-VAR methodologies when dealing with series exhibiting structural breaks.

Contrasting optical properties of dissolved organic matter between oceanic regions near the Getz and Dotson ice shelves in the Amundsen Sea, West Antarctica

The Amundsen Sea, located in West Antarctica, is experiencing rapid melting due to the intrusion of Circumpolar Deep Water, which is causing ice sheet thinning and basal melting. The resulting changes can affect the biogeochemical cycle of dissolved organic matter (DOM) by supplying iron from sea ice and/or glacier, thereby influencing primary production and ocean circulation. Therefore, it is crucial to understand the dynamics of the DOM in this region. In this study, our primary focus was to examine the optical properties of DOM in the oceanic regions adjacent to the West Getz Ice Shelf (WGIS) and the Dotson Ice Shelf (DIS). Significant differences in DOM optical properties, including the chromophoric DOM (CDOM) absorption coefficient at 350 nm (a350), spectral slope coefficient (S275–295), and specific UV absorbance at 254 nm (SUVA254), were observed between the WGIS and DIS regions (t-test, p < 0.05). Notably, the WGIS regions exhibited high a350 values. Additionally, the S275–295 and SUVA254 values, which serve as indices of molecular weight, indicated that the DOM pool in the WGIS regions was dominated by high molecular weight compounds with a substantial proportion of aromatic compounds. In contrast, the low values of a350 and SUVA254 along with the high S275–295 values in the DIS region suggested the dominance of low molecular weight CDOM associated with compounds of lower aromaticity. Furthermore, significant negative correlations were found between biomass of Phaeocystis antarctica (P. antarctica) and phosphate (PO4) in the WGIS regions (r2 = 0.82, p < 0.01 for WGIS 1 and r2 = 0.73, p < 0.01 for WGIS 2). However, no significant relationship was observed in the DIS region. These findings suggest that the high value and molecular weight of a350, extending from the surface layer to the deep layer, in the WGIS regions were associated with autochthonous sources, primarily driven by the colony-forming bloom of P. antarctica. These findings demonstrate that the quantity and quality of DOM in the Amundsen Sea are strongly affected by bloom conditions. The results emphasize that a combination of physical and biological processes interacts in complex ways to determine the characteristics of DOM in the Amundsen Sea.

The role of Fintech financing in correcting ecological problems caused by mineral resources: Testing the novel ecological deficit hypothesis

Mineral resource-abundant nations encounter different forms of ecological problems which necessitate these nations to come up with credible solutions. Hence, this study empirically explores how Fintech development affects the ecological statuses of leading mineral-exporting nations, in light of a novel ecological deficit hypothesis. In this regard, advanced panel data estimation methods that are adept in handling issues related to cross-sectional dependence, heterogeneous slope coefficients, and endogenous covariates are employed for analytical purposes. Overall, the findings obtained from the analysis highlight the importance of persistently scaling credit extensions to Fintech startup-based projects for ultimately shrinking the initial ecological deficit-widening impacts of Fintech development. Accordingly, the validity of the ecological deficit hypothesis is verified by the inverted U-shaped nexus between Fintech credits and ecological deficits. In addition, the mineral sector expansion-led deterioration in the ecological status is affirmed by the findings. Moreover, the pollution haven hypothesis in the context of ecological deficits is found to be valid while urbanization is observed to deteriorate the extent of ecological deficits in the selected mineral-exporting nations. Furthermore, the robustness of these findings is confirmed in most cases when ecological footprint and biocapacity are considered as the outcome variable instead of ecological deficits. In line with these key findings, it is deemed necessary for the concerned mineral-exporting nations to not only amplify their level of Fintech credit extensions but also increase its share of their respective national output levels. Besides, greening future mineral sector expansion-related policies is essential in further reducing the ecological deficits. Furthermore, attracting ecologically friendly foreign direct investments and adopting sustainable urbanization mechanisms should be considered by these mineral-exporting nations to become ecologically surplus in the future.

The apparent quantum yield matrix (AQY-M) of CDOM photobleaching in estuarine, coastal, and oceanic surface waters

The photochemical degradation of chromophoric dissolved organic matter (CDOM) upon solar exposure, known as photobleaching, can significantly alter the optical properties of the surface ocean. By leading to the breakdown of UV- and visible-radiation-absorbing moieties within dissolved organic matter, photobleaching regulates solar heating, the vertical distribution of photochemical processes, and UV exposure and light availability to the biota in surface waters. Despite its biogeochemical and ecological relevance, this sink of CDOM remains poorly quantified. Efforts to quantify photobleaching globally have long been hampered by the inherent challenge of determining representative apparent quantum yields (AQYs) for this process, and by the resulting lack of understanding of their variability in natural waters. Measuring photobleaching AQY is made challenging by the need to determine AQY matrices (AQY-M) that capture the dual spectral dependency of this process (i.e., magnitude varies with both excitation wavelength and response wavelength). A new experimental approach now greatly facilitates the quantification of AQY-M for natural waters, and can help address this problem. Here, we conducted controlled photochemical experiments and applied this new approach to determine the AQY-M of 27 contrasting water samples collected globally along the land-ocean aquatic continuum (i.e., rivers, estuaries, coastal ocean, and open ocean). The experiments and analyses revealed considerable variability in the magnitude and spectral characteristics of the AQY-M among samples, with strong dependencies on CDOM composition/origin (as indicated by the CDOM 275–295-nm spectral slope coefficient, S275–295), solar exposure duration, and water temperature. The experimental data facilitated the development and validation of a statistical model capable of accurately predicting the AQY-M from three simple predictor variables: 1) S275–295, 2) water temperature, and 3) a standardized measure of solar exposure. The model will help constrain the variability of the AQY-M when modeling photobleaching rates on regional and global scales.

Unravelling the genetic variability of host resilience to endo- and ectoparasites in Nellore commercial herds

BackgroundHost resilience (HR) to parasites can affect the performance of animals. Therefore, the aim of this study was to present a detailed investigation of the genetic mechanisms of HR to ticks (TICK), gastrointestinal nematodes (GIN), and Eimeria spp. (EIM) in Nellore cattle that were raised under natural infestation and a prophylactic parasite control strategy. In our study, HR was defined as the slope coefficient of body weight (BW) when TICK, GIN, and EIM burdens were used as environmental gradients in random regression models. In total, 1712 animals were evaluated at five measurement events (ME) at an average age of 331, 385, 443, 498, and 555 days, which generated 7307 body weight (BW) records. Of the 1712 animals, 1075 genotyped animals were used in genome-wide association studies to identify genomic regions associated with HR.ResultsPosterior means of the heritability estimates for BW ranged from 0.09 to 0.54 across parasites and ME. The single nucleotide polymorphism (SNP)-derived heritability for BW at each ME ranged from a low (0.09 at ME.331) to a moderate value (0.23 at ME.555). Those estimates show that genetic progress can be achieved for BW through selection. Both genetic and genomic associations between BW and HR to TICK, GIN, and EIM confirmed that parasite infestation impacted the performance of animals. Selection for BW under an environment with a controlled parasite burden is an alternative to improve both, BW and HR. There was no impact of age of measurement on the estimates of genetic variance for HR. Five quantitative trait loci (QTL) were associated with HR to EIM but none with HR to TICK and to GIN. These QTL contain genes that were previously shown to be associated with the production of antibody modulators and chemokines that are released in the intestinal epithelium.ConclusionsSelection for BW under natural infestation and controlled parasite burden, via prophylactic parasite control, contributes to the identification of animals that are resilient to nematodes and Eimeria ssp. Although we verified that sufficient genetic variation existed for HR, we did not find any genes associated with mechanisms that could justify the expression of HR to TICK and GIN.

Factors associated with enteral autonomy after reanastomosis in infants with intestinal failure and ostomy: A descriptive cohort study.

To determine variables associated with outcomes in infants with intestinal failure (IF) and ostomy following reanastomosis (RA). A single-center, descriptive cohort study of 120 infants with IF and a stoma from January 2011 to December 2020 with subsequent RA during initial hospitalization. The primary outcome was achievement of enteral autonomy (EA) following RA. Other outcomes were duration of hospital stay, and mortality. Penalized logistic regression and linear regression were used for data analysis. The median gestational age was 26 weeks, and the median birth weight was 890 g. Three infants died. The median duration between ostomy creation and RA was 80 days (interquartile range; 62.5, 100.5). For each additional day of discontinuity, the odds of EA decreased by 2% (odds ratio [OR] = 0.980; 95% confidence interval [CI]: 0.962, 0.999; P = 0.038), and death increased by 4.2% (OR = 1.042; 95% CI: 1.010, 1.075; P = 0.009). For each additional mL/kg/day of enteral feeds at RA, the odds of EA increased by 7.5% (OR = 1.075; 95% CI: 1.027, 1.126, P = 0.002) and duration of hospital stay decreased by 0.35 days (slope coefficient = -0.351; 95% CI: -0.540, -0.163; P < 0.001). Shorter duration of intestinal discontinuity and enteral nutrition before RA could positively influence EA and duration of stay in infants with IF and ostomy following RA.

An empirical re-investigation for verifying the pollution haven hypothesis concerning the foreign direct investment-carbon intensity nexus: Contextual evidence from BRICS

Since the BRICS countries make noteworthy contributions to global economic outputs and also account for around half of the total volume of carbon dioxide emitted worldwide, greening the economic growth processes and facilitating clean energy transition across these emerging nations have significant relevance at the global scale. Therefore, this study aims to assess the long-run determinants of carbon intensity levels of economic output and energy use in the context of the BRICS countries over the period spanning from 1998 to 2021. Specifically, this analysis is conceptualized to examine the non-linear carbon intensity-influencing impacts of incoming foreign direct investment through the lens of the widely-acclaimed pollution haven hypothesis, while controlling for other major macroeconomic factors. In this regard, advanced panel data estimators that are robust to negating issues related to cross-sectional dependence, heterogeneous slope coefficients, and endogeneity are utilized. In a nutshell, the results ultimately verify the pollution haven hypothesis by confirming the inverted U-shaped nexus between foreign direct investment inflows and carbon intensity levels of economic output. On the other hand, incoming foreign direct investment is found to monotonically increase, albeit at a decreasing rate, the carbon intensity levels of energy use. Besides, more renewable energy deployment and technological progress are identified as carbon intensity-inhibiting factors while institutional quality improvement, financial development, and international trade are responsible for amplifying carbon intensity levels, especially those related to economic output production. Hence, based on these findings, several policies are recommended for the BRICS countries to gradually green their economic growth processes and successfully undergo the clean energy transition so that their future carbon intensity levels can be contained to a large extent. These findings are expected to guide the BRICS nations in enhancing compliance with the pledges they made by signing the 2030 Sustainable Development Goals agenda of the United Nations.

A Comprehensive Investigation into the Money Demand Function in Cambodia: An Empirical Analysis

The objective of this study is to establish a money demand function in Cambodia. The findings obtained through the ARDL approach to cointegration indicate that real income, consumer price index, and interest rate are cointegrated with real money demand. In terms of the estimated results derived from the long-run model, it is observed that real income has a statistically significant positive impact on real money demand, while the general price level and interest rate have a negative impact. The short-run dynamic model, known as the error correction model, demonstrates that all explanatory variables collectively account for the growth rate of real money balances. In the short-run, the growth rate of real income exhibits a positive relationship with the demand for real money, whereas the inflation rate and changes in interest rate have a significant negative effect on the demand for real money balances. The estimated slope coefficient of the short-run dynamic model, which measures the speed of adjustment, is projected to be 60.67%. This outcome suggests that the real money balance model takes no more than two quarters to adjust towards long-run equilibrium in response to short-run dynamic shocks. Stability tests, such as the CUSUM and CUSUMSQ tests, indicate that the real money demand function in Cambodia remains stable in the long-term. The findings derived from this study provide empirical evidence in favor of the quantity theory of money.

Impacts of Human Activities on the Net Primary Productivity of Vegetation in Chengde's Transitional Region from Plateau to Plain in the Context of Climate Change

Chengde's transitional region from plateau to plain is located in the transition zone of agriculture and livestock and is extremely sensitive to climate change and human activities. This study used the net primary productivity(NPP) of vegetation as an evaluation index to quantify the degree impacts of climate change and human activities on vegetation change in the region. The Thornthwaite Memorial model was used to calculate the potential NPP, and the actual NPP was obtained based on MODIS NPP remote sensing images, using the difference between the actual and potential NPPs to express the amount of change in NPP owing to human activities. We used the slope trend and coefficient of variation method to analyze the trend and stability distribution of the actual NPP, potential NPP, and NPP influenced by human activities, and the correlation between actual NPP and annual precipitation and annual average temperature was analyzed using the correlation coefficient method. Finally, we quantified the impact of climate change and human activities on vegetation change in the region. The results showed that 99.87% of the vegetation in the region was improved and changed steadily, and the proportions of the areas showing positive correlation between actual NPP and annual precipitation and annual average temperature were 99.87% and 91.66%, respectively. The potential NPP showed an increasing trend from northwest to southeast, whereas the trend and stability of the potential NPP both showed an increasing trend from west to east. The area where climate change and human activities played a role in vegetation improvement accounted for 99.71%, and that affected by climate change accounted for 0.14%, with the proportion of human activities leading to vegetation degradation being 0.15%.

Nonparametric Gini-Frisch bounds

The Gini-Frisch bounds partially identify the constant slope coefficient in a linear equation when the explanatory variable suffers from classical measurement error. This paper generalizes these quintessential bounds to accommodate nonparametric heterogeneous effects. It provides suitable conditions under which the main insights that underlie the Gini-Frisch bounds apply to partially identify the average marginal effect of an error-laden variable in a nonparametric nonseparable equation. To this end, the paper puts forward a nonparametric analogue to the standard “forward” and “reverse” linear regression bounds. The nonparametric forward regression bound generalizes the linear regression “attenuation bias” due to classical measurement error.

Neural network spectral relationship to improve an inherent optical properties data processing system for residual error correction.

The residual error was a critical indicator to measure the data quality of ocean color products, which allows a user to decide the valuable envisioned application of these data. To effectively remove the residual errors from satellite remote sensing reflectance (Rrs) using the inherent optical data processing system (IDAS), we expressed the residual error spectrum as an exponential plus linear function, and then we developed neural network models to derive the corresponding spectral slope coefficients from satellite Rrs data. Coupled with the neural network models-based spectral relationship, the IDAS algorithm (IDASnn) was more effective than an invariant spectral relationship-based IDAS algorithm (IDAScw) in reducing the effects of residual errors in Rrs on IOPs retrieval for our synthetic, field, and Chinese Ocean Color and Temperature Scanner (COCTS) data. Particularly, due to the improved spectral relationship of the residual errors, the IDASnn algorithm provided more accurate and smoother spatiotemporal ocean color product than the IDAScw algorithm for the open ocean. Furthermore, we could monitor the data quality with the IDASnn algorithm, suggesting that the residual error was exceptionally large for COCTS images with low effective coverage. The product effective coverage should be rigorously controlled, or the residual error should be accurately corrected before temporal and spatial analysis of the COCTS data. Our results suggest that an accurate spectral relationship of residual errors is critical to determine how well the IDAS algorithm corrects for residual error.

Effect of Diabetes type-II on Eye disease and its risk factors; A Logit Model Analysis

To know the effect of Diabetes type-II on Eye disease and its risk factors in a tertiary eye care hospital in Karachi. This was a cross-sectional study with retrospective data collection. The data was retrieved from January to June 2019 from the Hospital Information Management System (HIMS) software of the Institute. Non-probability purposive sampling method was used to collect data. Inclusion criteria were all the diabetics type-II patients came for routine check-ups at Diabetes Eye Department irrespective of age, gender and duration of diabetes. Statistical analysis was done using STATA version 13.0 software for windows. A total of 6090 cases were analyzed. Mean age of the participants was 51.01±10.8 years. There were 2954 (48.5%) male and 3136 (51.5%) female observed in this study. Table 1 shows the results of the binary logistic regression analysis with coefficients and their standard errors (S.E.), Wald test values, p values, odd ratios, and 95% confidence intervals for odds ratios. When all explanatory variables treat as continuous variables, we found that all variables which include age, height, random blood sugar (RBS) and duration of diabetes was statistically significant at the significance level 0.05 except weight and fasting blood sugar (FBS) for individual regression slope coefficients. This study reveals findings through binary logistics regression analysis. It indicates that there is an association found in the patients of eye disease with age, height, weight, RBS, FBS. This stated that there were some risk factors observed in these variables related to eye disease. Those who have the disease have risk factor to developed the others associated disease.

Have the effects of shocks to oil price expectations changed?: Evidence from heteroskedastic proxy vector autoregressions

Studies of the crude oil market based on structural vector autoregressive (VAR) models typically assume a time-invariant model and transmission of shocks and possibly allow for heteroskedasticity by using robust inference procedures. We assume a heteroskedastic reduced-form VAR model with time-invariant slope coefficients and explicitly consider the possibility of time-varying shock transmission due to heteroskedasticity. We study a model for the global crude oil market that includes key world and U.S. macroeconomic variables and find evidence for changes in the transmission of shocks to oil price expectations during the last decades which can be attributed to heteroskedasticity.

Metoda obliczania jednostkowego składu węglowodorów na podstawie skumulowanego składu frakcyjnego próbek ropy naftowej i kondensatu

The composition of oils is the main source of information that enables the evaluation and modeling of their physical, thermal and chemical properties (including their critical properties) across a wide range of state parameters. The more comprehensively the composition of oils is analyzed, the more precise information is provided for calculations and problem-solving in the field of oilfield mechanics and related areas, such as the extraction, preparation, transportation, and processing of oils and their fractions. The principal constituents of oils are hydrocarbons. Oils contain hydrocarbons of three homologous series: paraffins, naphthenes and aromas. In oils, there may be hydrocarbons of a mixed composition containing both naphthenic and aromatic rings. In addition to hydrocarbons, oils also contain oxygen, sulfur, nitrogen and other constituents. These compounds are the primary elements of asphaltene-resinous substances (ARS) found in oil. They are characterized by high relative densities (often exceeding 1 g/cm3), dark coloration, and relative chemical instability when exposed to elevated temperatures, oxygen, adsorbents, etc. The composition of asphaltene-resinous substances encompasses a wide range of substances. The validity of the proposed technique is justified by the observation that the data of molecular weight, Watson characteristic factor, and experimental density calculated from molar compositions should align on the same surface with a high degree of correlation. In addition, the experimental and calculated values, in terms of molecular composition, of molecular weights should lie on a straight line passing through the origin of coordinates with a slope coefficient equal to unity and exhibit high degree of correlation.

탈세계화가 아태지역 국가의 경제성장에 미치는 영향에 관한 연구

Purpose - The WTO and World Bank have pointed out the phenomenon of deglobalization. Despite this, Asian countries are pursuing closer cooperation with other countries in the region and around the world. Accordingly, this study analyzes the impact of deglobalization on the economic growth of Asia-Pacific countries through non-linear relationships. We use 33 Asia-Pacific nation’s panel data from 1990, when globalization rapidly increased, to 2020, when deglobalization saw progress.&#x0D; Design/Methodology/Approach - We analyze the spatial panel regression model using the AMG (Augmented Mean-Group) estimation method, which controls for cross-sectional dependence between countries in panel data and country-specific slope coefficient heterogeneity in the panel model.&#x0D; Findings - As a result of the estimation, there is an inverted U-shaped relationship between deglobalization and Asia-Pacific economic growth. As deglobalization occurs up to 50.11%, economic growth increases, but as deglobalization continues past 50.11%, economic growth decreases.&#x0D; Research Implications - Countries with less deglobalization must increase economic growth through policies that protect their own industries, and countries whose level of deglobalization exceeds the threshold must open international relations and pursue economic growth through mutual cooperation and economic integration. In the long term, deglobalization threatens Asia's integrated development and sustainable growth, so globalization, free trade, and multilateralism must be maintained.

An Assessment of Turkish Inflation Dynamics Based on Phillips Curve Variants With Import Price Index

This study aims to present an assessment on Phillips curve models based on import price index in order to account for inflation dynamics in Turkey over the period 2002Q1:2021Q1 by employing state-space approach in potential output computations. In order to deal with the expectation terms in estimating equations and to avoid the associated endogeneity issue, the Generalized Method of Moments (GMM) technique has been used, and two distinct measures of output gap based on Hodrick-Prescott filter and Kalman Filter algorithm have been performed. First, the time varying slope coefficients regarding traditional hybrid Phillips curve (PC) have been estimated through rolling window approach for Turkey. Then, two variants of the hybrid PCs have been formulated by including import price index regressor to all of them and the forecasting performances of the models have been evaluated.

Panel Regression Modelling for COVID-19 Infections and Deaths in Tamil Nadu, India

The impacts of the coronavirus disease 2019 (COVID-19) pandemic have been extremely severe, with both economic and health crises experienced worldwide. Based on the panel regression model, this study examined the trends and correlations in the number of COVID-19-related deaths and the number of COVID-19-infected cases in all 37 regions of the Tamil Nadu state in India, in August 2020. The fixed effects model had the greatest R2 value of 78% and exhibited significant results. The slope coefficient was also highly significant, showing a considerable variation in the relationship between new COVID-19 cases and deaths. Additionally, for every unit increase in COVID-19-infected cases, the death rate increased by 0.02%.