scholarly journals New Methods in Exploring Old Topics: Case Studying Brittle Diabetes in the Family Context

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Moritz Philipp Günther ◽  
Peter Winker ◽  
Stefan A. Wudy ◽  
Burkhard Brosig
Keyword(s):  
Quantitative Research ◽  
Time Series Data ◽  
Selection Process ◽  
Glycemic Variability ◽  
Series Data ◽  
Research Approach ◽  
Affective States ◽  
Brittle Diabetes ◽  
Qualitative Approaches ◽  
Lag Selection

Background. In questing for a more refined quantitative research approach, we revisited vector autoregressive (VAR) modeling for the analysis of time series data in the context of the so far poorly explored concept of family dynamics surrounding instable diabetes type 1 (or brittle diabetes).Method. We adopted a new approach to VAR analysis from econometrics referred to as the optimized multivariate lag selection process and applied it to a set of raw data previously analyzed through standard approaches.Results. We illustrated recurring psychosomatic circles of cause and effect relationships between emotional and somatic parameters surrounding glycemic control of the child’s diabetes and the affective states of all family members.Conclusion. The optimized multivariate lag selection process allowed for more specific, dynamic, and statistically reliable results (increasingR2tenfold in explaining glycemic variability), which were derived from a larger window of past explanatory variables (lags). Such highly quantitative versus historic more qualitative approaches to case study analysis of psychosomatics surrounding diabetes in adolescents were reflected critically.

scholarly journals Analysis The Effect of Electronic Money Use on Velocity of Money: Evidence from Indonesia

2020 ◽  
Vol 5 (1) ◽  
pp. 42
Author(s):  
Sufi Azhari Pambudi ◽  
M. Khoerul Mubin
Keyword(s):  
Interest Rates ◽  
Quantitative Research ◽  
Time Series Data ◽  
Series Data ◽  
Research Approach ◽  
Electronic Money ◽  
Correction Model ◽  
Income Levels ◽  
Long Run ◽  
Velocity Of Money

This study aims to examine the effect of electronic money transactions on the velocity of money in Indonesia. This study uses a quantitative research approach using quarterly time series data for the 2010q1-2018q4 period. Using variable velocity obtained from Gross Domestic Product (GDP) divided by M2, electronic money transactions, GDP per capita, and interest rates using the Error Correction Model (ECM) method. The results show that in the long run variable electronic money transactions, income levels and interest rates are significantly positive. In the short term, interest rates and income levels are significantly positive, while electronic money transactions only have a slight effect on the velocity of moneyin Indonesia.

scholarly journals A quantitative assessment of the impact of government activities on the economy of Poland

2019 ◽  
Vol 6 (2) ◽  
pp. 220-233
Author(s):  
Daniel Francois Meyer
Keyword(s):  
Economic Growth ◽  
Government Spending ◽  
Quantitative Research ◽  
Time Series Data ◽  
Positive Impact ◽  
Primary Objective ◽  
Series Data ◽  
Research Approach ◽  
Causality Analysis ◽  
The Impact

Government interventions and economic activities could have significant impacts on the economies of countries. Effective governance and quality institutions are required for sustainable economic growth in both developed and developing countries. The primary objective of this study was to analyse the impact of government activities on economic growth in Poland. The study followed a quantitative research approach, employing time series data from 1995 to 2017 including GDP as the dependent variable with variables such as government spending and debt, size and effectiveness of government, and the level of corruption as independent variables. The relationships between the variables were analysed by making use of an Auto Regressive Distributed Lag (ARDL) econometric model. The results indicated that there are both long- and short-run relationships between the variables. Other results indicated that government variables included in the study, caused changes in economic growth as assessed via a Granger causality analysis. A number of recommendations were listed which include inter alia, that effective government spending and management have a positive impact on the economy, while efforts to limit the levels of corruption also contributes to economic improvements in a country.

scholarly journals An assessment of the interrelations between country risk, economic growth and good governance: The case of the Visegrád four

2021 ◽  
Vol 8 (4) ◽  
pp. 610-627
Author(s):  
Daniel Francois Meyer
Keyword(s):  
Risk Factors ◽  
Economic Growth ◽  
Economic Performance ◽  
Quantitative Research ◽  
Time Series Data ◽  
Good Governance ◽  
Risk Index ◽  
Country Risk ◽  
Series Data ◽  
Short Run

nvestors assess the environment and the level of risk before they invest in a specific region or country. Several country risk indexes have been developed since the beginning of the 1990s, using risk factors such as politics, the economy and sovereign risk factors. This study aims to determine the relationships between the country risk index, economic performance and good governance. The study implemented a quantitative research methodology with panel data, focusing on the four Visegrad countries, using time-series data from 1996 to 2019. The results indicate both long- and short-run relationships. Both GDP and good governance significantly impact the country risk index with coefficients of between 0.17 to 0.31 and 0.02 to 0.15 according to different estimation models. The Granger causality results indicated that both GDP and good governance cause changes in the country risk indexes of the countries, and good governance causes increased economic performance. In conclusion, the study showed clear evidence that a lower country risk index is important to attract investment and sustained economic growth and good governance is critical in this process.          

scholarly journals MENINGKATKAN KINERJA KEUANGAN RETURN ON EQUITY (ROE) MELALUI RASIO STRUKTUR MODAL DEBT TO ASSET RATIO (DAR) DAN DEBT TO EQUITY RATIO (DER) PADA PT BANK MANDIRI TBK YANG TERDAFTAR DI BURSA EFEK INDONESIA

2021 ◽  
Vol 12 (1) ◽  
pp. 52-65
Author(s):  
Armalinda Armalinda
Keyword(s):  
Financial Performance ◽  
Quantitative Research ◽  
Time Series Data ◽  
Stock Exchange ◽  
Statistical Tests ◽  
Financial Statements ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Return On Equity ◽  
Equity Ratio

This study aims to determine how much influence the Debt to Assets Ratio (DAR) and Debt to Equity Ratio (DER) have on the Return on Equity (ROE) of PT Bank Mandiri Tbk which are listed on the Indonesia Stock Exchange. The research design used in this research is associative/quantitative research. The population in this study is the annual financial statements of PT. Bank Mandiri Tbk for the period 2012-2019, while the sample was taken using time series data, namely the annual financial statements of PT. Bank Mandiri Tbk for the period 2012-2019 which consists of balance statements, income statements, and cash flow from funding activities from 2012 to 2019. The result of the coefficient of determination (R Square) is 0.813. This figure means that 0.813 or 81.3% of the diversity of data from financial performance data can be explained by the two independent variables, namely the Debt to Asset Ratio and the Debt to Equity Ratio. While the rest (1-0.813 = 0.817) or 18.7% is explained by other factors outside the study. The results of statistical tests show that the Asset Ratio and Debt to Equity Ratio together (simultaneously) have an effect on financial performance (Return on Equity).

Analisis pengaruh makroekonomi terhadap dana pihak ketiga (DPK) dengan equivalent rate (ER) sebagai variabel intervening

2021 ◽  
pp. 100-123
Author(s):  
Salma Firdayanti Salma ◽  
Yusvita Nena Arinta Nena
Keyword(s):  
Exchange Rate ◽  
Quantitative Research ◽  
Time Series Data ◽  
Secondary Data ◽  
Third Party ◽  
Series Data ◽  
Equivalent Rate ◽  
Negative Effect ◽  
Party Funding

This study aims to determine the Effect of Macroeconomics on Third-Party Funding (TPF) with the Equivalent Rate (ER) as the Intervening Variable (Case Study of Islamic Commercial Banks Period 2016-2020). This type of research is quantitative research which utilizes secondary data in the form of time-series data. Purposive sampling was used as the sampling method. The data that has been obtained later processed using the E-views version 9 application tool. Based on the results, it is shown that the Inflation, BI Rate, and Equivalent Ratevariables partially have a negative effect on TPF, while the Exchange Rate has a positive effect on TPF. Moreover, the variables of Inflation, Exchange Rate, and BI Rate have a positive and significant effect on the Equivalent Rate (ER). It is also found thatThe Equivalent Rate variable cannot mediate the effect of Inflation, Exchange Rate, and BI Rate on TPF.

scholarly journals Moderation of Non Performing Financing on Natural Uncertainty Contracts To The Profitability of Islamic Commercial Bank In Indonesia

2020 ◽  
Vol 4 (02) ◽  
Author(s):  
Taudlikhul Afkar ◽  
Grahita Chandrarin ◽  
Lilik Pirmaningsih
Keyword(s):  
Structural Equation ◽  
Quantitative Research ◽  
Time Series Data ◽  
Equation Model ◽  
Series Data ◽  
Islamic Banks ◽  
Business Managers ◽  
Quantitative Research Methods ◽  
Research Results ◽  
Analysis Technique

This study intends to provide an overview of the consistency of research results with theoretical and empirical points of view, it is done because many research results are inconsistent with the theory. Quantitative research methods are used to make generalizations using a sample of 14 Islamic Commercial Banks in Indonesia with time series data collection techniques for 5 years. The data analysis technique used is multivariate analysis using the Warp PLS structural equation model. The results showed that the level of profitability of Islamic banks is always overshadowed by the occurrence of credit risk that causes non-performing financing from financing of the type of natural uncertainty contracts because it is type of financing is a financing that does not provide certainty of results. The results of this study are consistent with agency theory that explains the existence of information asymmetry, and consistent with the theory of mixing that by providing opportunities to manage business to business managers (mudharib/mustyarik) without interference from the owner of the fund (shaibul maal) can lead to the risk of default and thus affect the ability of Islamic banks to obtain profitability.

scholarly journals PENGARUH PERTUMBUHAN EKONOMI TERHADAP KESEMPATAN KERJA DI PROVINSI SULAWESI TENGGARA

2018 ◽  
Vol 6 (2) ◽  
pp. 54
Author(s):  
Muhammad Nur Afiat
Keyword(s):  
Economic Growth ◽  
Quantitative Research ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Secondary Data ◽  
Least Square Method ◽  
Multiple Linear Regression Analysis ◽  
Least Square ◽  
Series Data ◽  
Employment Opportunities

This study was conducted with the aim to determine the effect of Economic Growth Rate on Employment Opportunities in Southeast Sulawesi Province 2000-2015. This research is a type of Quantitative research using secondary data in the form of time series data, ie from 2000-2015. Data source was obtained from Central Bureau of Statistics (BPS) and Bank Indonesia of Southeast Sulawesi Province. This study also uses multiple linear regression analysis tools with ordinary least square method (OLS) and then processed with application Eviews 8.0. The results of the study show that Economic Growth has a significant influence on Employment Opportunities in Southeast Sulawesi Province 2000-2015.

scholarly journals THE PRICE MECHANISM FUNCTION OF CURLY RED CHILLY IN THE CENTER OF PRODUCTION AND WHOLESALER

2020 ◽  
Vol 1 (3) ◽  
pp. 466-470
Author(s):  
Dety Sukmawati ◽  
Ning Srimenganti
Keyword(s):  
Time Series ◽  
Quantitative Research ◽  
Time Series Data ◽  
Rational Expectation ◽  
Series Data ◽  
High Price ◽  
Price Information ◽  
Price Increases ◽  
Crop Agriculture ◽  
Price Analysis

The problem of red chili related to price fluctuations has always been a concern for farmers.Therefore, an increase in the production of agricultural commodities including chili horticultural commodities needs to be accompanied by improvements to the marketing system. These research was  quantitative research, data collection was done by means of a survey of time series .  The data used are time series data and supporting data which come from: Information center of price at production center, and price information at West Java Food Crop Agriculture Agency. From the amount of data (included observation) which amounted to 72 data. The technic analyzed used multivariate. ,the rational expectation hypothesis of the supply function was analyzed by the EVIEWS 8. the results of price analysis in Cikajang have a dominant influence on prices in the PIKJ and vice versa, the results of the analysis show that an increase in price of 1 rupiah in Cikajang will increase the price in PIKJ 0.7679 rupiah, or an increase in price of 76.79% meaning an increase in prices in production centers will raised the price of 76.79% in the PIKJ. PIKJ will quickly respond to price increases in production centers even though the distance from production centers to PIKJ was very far, the flow of price information that occurs was actually one-way from PIKJ to production centers. The response to the high price increase was seen that the PIKJ was a price determinant and when viewed from the marketing actors involved in it turns out there were farmers in the production center which were dealers or traders in the PIKJ.

On the Autoregressive Time Series Model Using Real and Complex Analysis

Forecasting ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 716-728
Author(s):  
Torsten Ullrich
Keyword(s):  
Time Series ◽  
Model Selection ◽  
Closed Form ◽  
Autoregressive Model ◽  
Complex Analysis ◽  
Time Series Data ◽  
Selection Process ◽  
Global Structure ◽  
Series Data ◽  
Time Step

The autoregressive model is a tool used in time series analysis to describe and model time series data. Its main structure is a linear equation using the previous values to compute the next time step; i.e., the short time relationship is the core component of the autoregressive model. Therefore, short-term effects can be modeled in an easy way, but the global structure of the model is not obvious. However, this global structure is a crucial aid in the model selection process in data analysis. If the global properties are not reflected in the data, a corresponding model is not compatible. This helpful knowledge avoids unsuccessful modeling attempts. This article analyzes the global structure of the autoregressive model through the derivation of a closed form. In detail, the closed form of an autoregressive model consists of the basis functions of a fundamental system of an ordinary differential equation with constant coefficients; i.e., it consists of a combination of polynomial factors with sinusoidal, cosinusoidal, and exponential functions. This new insight supports the model selection process.

scholarly journals Evaluating the Performance of Multiple Imputation Methods for Handling Missing Values in Time Series Data: A Study Focused on East Africa, Soil-Carbonate-Stable Isotope Data

Stats ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 457-467 ◽  
Author(s):  
Hossein Hassani ◽  
Mahdi Kalantari ◽  
Zara Ghodsi
Keyword(s):  
Time Series ◽  
East Africa ◽  
Quantitative Research ◽  
Missing Values ◽  
Time Series Data ◽  
Extreme Values ◽  
Singular Spectrum Analysis ◽  
Series Data ◽  
Data Set ◽  
Imputation Methods

In all fields of quantitative research, analysing data with missing values is an excruciating challenge. It should be no surprise that given the fragmentary nature of fossil records, the presence of missing values in geographical databases is unavoidable. As in such studies ignoring missing values may result in biased estimations or invalid conclusions, adopting a reliable imputation method should be regarded as an essential consideration. In this study, the performance of singular spectrum analysis (SSA) based on L 1 norm was evaluated on the compiled δ 13 C data from East Africa soil carbonates, which is a world targeted historical geology data set. Results were compared with ten traditionally well-known imputation methods showing L 1 -SSA performs well in keeping the variability of the time series and providing estimations which are less affected by extreme values, suggesting the method introduced here deserves further consideration in practice.

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