Time Series Analysis of the Sex Composition of the Unemployed.

1983 ◽  
Vol 26 ◽  
pp. 153-178
Author(s):  
S. Haberman
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Social Insurance ◽  
Unemployment Benefit ◽  
Series Analysis ◽  
General Terms ◽  
Run Off ◽  
The Future ◽  
The Government ◽  
The Unemployed

This paper describes the use of time series analysis in the solution of a problem arising in social insurance. As part of a model which estimates the future cost of unemployment benefit the Government Actuary's Department (GAD) is required to forecast the proportion of the unemployed in future calendar quarters, who are male. The format of the paper is to describe forecasting in general terms in §1 and the particular problem under consideration in §2. In subsequent sections, the data available (§ 3), the existing forecasting model (§ 4) and alternative time series models (§§ 5–8) are described. The everyday job of the actuary involves the estimation of a future series of events. Examples include the estimation of future streams of liability outgo and asset income in life assurance, the run-off of outstanding claims in nonlife insurance, and the future numbers of persons in a subgroup of the total population. This estimation can be qualitative or quantitative, short-term or long-term, deterministic or stochastic and will involve the establishment of a mathematical-statistical model, and the determination of the relevant parameters by an analysis of the data available.

Analyses and anticipating the future trend of accidents in an electricity distribution company of Iran: A time series analysis

Work ◽  
2021 ◽  
pp. 1-6
Author(s):  
Shirin Nasrollah Nejhad ◽  
Tayebeh Ilaghinezhad Bardsiri ◽  
Maryam feiz arefi ◽  
Amin babaei poya ◽  
Ehsan mazloumi ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Occupational Injuries ◽  
Model Management ◽  
High Rate ◽  
Electricity Distribution ◽  
Temporary Workers ◽  
Series Analysis ◽  
The Future ◽  
Distribution Company

BACKGROUND: Many work-related fatalities happen every year in electricity distribution companies. This study was conducted to model accidents using the time series analysis and survey descriptive factors of injuries in an electricity distribution company in Tehran, Iran. METHODS: Data related to 2010 to 2017 were collected from the database of the safety department. Time Series and trend analysis were used for data analyzing and anticipating the accidents up to 2022. RESULT: Most of the accidents occurred in summer. Workers’ negligence was the reason for 75%of deaths. Employment type and type of injuries had a significant relationship (p <  0.05). CONCLUSION: The anticipating model indicated occupational injuries are going to have an increase in the future. A high rate of accidents in summer maybe because of the warm weather or insufficient skills in temporary workers. Temporary workers have no chance to work in a year like permanent workers, therefore acquisition experiences may be less in them. Based on the estimating model, Management should pay attention to those sectors of the company where most of the risky activities take place. Also, training programs and using personal protective equipment can help to protect workers in hazardous conditions.

scholarly journals A Time Series Analysis of the Nexus Between Macroeconomic Fundamentals and Stock Prices in Nigeria

2018 ◽  
Vol 13 (2) ◽  
pp. 69-91
Author(s):  
Amassoma Ditimi ◽  
Bolarinwa Ifeoluwa
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Stock Market ◽  
Time Series Analysis ◽  
Stock Prices ◽  
Macroeconomic Factors ◽  
Series Analysis ◽  
Integration Test ◽  
Macroeconomic Fundamentals ◽  
The Government

AbstractSince macroeconomic fundamentals have been found to play a vital role for changes in the economy of a country. Consequently, the onus is on the appropriate regulatory authorities to take measures in making amendments in these policies to put the economy on the right development track. The aim of this study is to use time series analysis to empirically showcase the nexus between macroeconomic fundamentals and stock prices in Nigeria. The method used for this study was the Co-integration test and the EGARCH technique to estimate the possible influence of the selected macroeconomic fundamentals on stock prices. Volatility was captured by using quarterly data and estimated using GARCH (1,1) respectively. The study found there is a positive relationship between macroeconomic factors and stock prices in Nigeria. Therefore, the study recommends that the Federal authority should put in place policy measures that will enable the exchange rate to be relatively stabilized. This is because empirical evidence from studies has shown that exchange rate affects stock market prices. In addition, the government authority should ensure an enabling environment that would build the mindset of institutional investors in the Nigerian stock market due to the existence of information asymmetry problems among potential investors.

scholarly journals STUDY OF THE INFLUENCE OF CHANGING THE PARAMETERS OF THE ARIMA MODEL ON THE QUALITY OF THE FORECAST FOR SHORT DATA SETS

2021 ◽  
Vol 21 (3) ◽  
pp. 36-46
Author(s):  
M.N. Fel’ker ◽  
◽  
V.V. Chesnov
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Arima Model ◽  
Annual Data ◽  
Data Sets ◽  
Arima Models ◽  
Data Set ◽  
Series Analysis ◽  
The Future

Time series, i.e. data collected at various times. The data collection segments may differ de-pending on the task. Time series are used for decision making. Time series analysis allows you to get some result that will determine the format of the decision. Time series analysis was carried out in very ancient times, for example, various calendars became a consequence of the analysis. Later, time series analysis was applied to study and forecast economic, social and other systems. Time se-ries appeared a long time ago. Once upon a time, ancient Babylonian astronomers, studying the po-sition of the stars, discovered the frequency of eclipses, which allowed them to predict their appearance in the future. Later, the analysis of time series, in a similar way, led to the creation of various calen-dars, for example, harvest calendars. In the future, in addition to natural areas, social and economic ones were added. Aim. Search for classification patterns of time series, allowing to understand whether it is possible to apply the ARIMA model for their short-term (3 counts) forecast. Materials and methods. Special software with ARIMA implementation and all need services is made. We examined 59 data sets with a short length and step equal a year, less than 20 values in the paper. The data was processed using Python libraries: Statsmodels and Pandas. The Dickey – Fuller test was used to de-termine the stationarity of the series. The stationarity of the time series allows for better forecasting. The Akaike information criterion was used to select the best model. Recommendations for a rea-sonable selection of parameters for adjusting ARIMA models are obtained. The dependence of the settings on the category of annual data set is shown. Conclusion. After processing the data, four categories (patterns) of year data sets were identified. Depending on the category ranges of parame-ters were selected for tuning ARIMA models. The suggested ranges will allow to determine the starting parameters for exploring similar datasets. Recommendations for improving the quality of post-forecast and forecast using the ARIMA model by adjusting the settings are given.

scholarly journals Impact of COVID-19 on routine malaria indicators in rural Uganda: an interrupted time series analysis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Jane F. Namuganga ◽  
Jessica Briggs ◽  
Michelle E. Roh ◽  
Jaffer Okiring ◽  
Yasin Kisambira ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Case Management ◽  
Malaria Diagnosis ◽  
Prevalence Ratio ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Outpatient Visits ◽  
The Government

Abstract Background In March 2020, the government of Uganda implemented a strict lockdown policy in response to the COVID-19 pandemic. Interrupted time series analysis (ITSA) was performed to assess whether major changes in outpatient attendance, malaria burden, and case management occurred after the onset of the COVID-19 epidemic in rural Uganda. Methods Individual level data from all outpatient visits collected from April 2017 to March 2021 at 17 facilities were analysed. Outcomes included total outpatient visits, malaria cases, non-malarial visits, proportion of patients with suspected malaria, proportion of patients tested using rapid diagnostic tests (RDTs), and proportion of malaria cases prescribed artemether-lumefantrine (AL). Poisson regression with generalized estimating equations and fractional regression was used to model count and proportion outcomes, respectively. Pre-COVID trends (April 2017-March 2020) were used to predict the’expected’ trend in the absence of COVID-19 introduction. Effects of COVID-19 were estimated over two six-month COVID-19 time periods (April 2020-September 2020 and October 2020–March 2021) by dividing observed values by expected values, and expressed as ratios. Results A total of 1,442,737 outpatient visits were recorded. Malaria was suspected in 55.3% of visits and 98.8% of these had a malaria diagnostic test performed. ITSA showed no differences between observed and expected total outpatient visits, malaria cases, non-malarial visits, or proportion of visits with suspected malaria after COVID-19 onset. However, in the second six months of the COVID-19 time period, there was a smaller mean proportion of patients tested with RDTs compared to expected (relative prevalence ratio (RPR) = 0.87, CI (0.78–0.97)) and a smaller mean proportion of malaria cases prescribed AL (RPR = 0.94, CI (0.90–0.99)). Conclusions In the first year after the COVID-19 pandemic arrived in Uganda, there were no major effects on malaria disease burden and indicators of case management at these 17 rural health facilities, except for a modest decrease in the proportion of RDTs used for malaria diagnosis and the mean proportion of malaria cases prescribed AL in the second half of the COVID-19 pandemic year. Continued surveillance will be essential to monitor for changes in trends in malaria indicators so that Uganda can quickly and flexibly respond to challenges imposed by COVID-19.

scholarly journals A Time Series Analysis and Forecasting of Opening Stock Price of McDonalds Crop.

2016 ◽  
Vol 12 (4) ◽  
pp. 6171-6177
Author(s):  
Rawiyah Muneer Alraddadi
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Fast Food ◽  
Stock Price ◽  
Ice Cream ◽  
Series Analysis ◽  
Different Types ◽  
The Future ◽  
Future Condition

McDonalds Corp. is globally famous and is abounded in recent years. It is one of the major chain restaurants that offers a fast food. Basic foods that are served at McDonalds are different types and sizes of burgers, fries, some breakfast, sweets, ice cream and kids meals. McDonalds products have increased loyalty from customers, which has led to the rise of an uneven stock price. So the data is not stationary and makes the role of the analysts ability to forecast the future condition of the organization important. The aim of this paper is to analyze and forecast the opening stock price of McDonalds Corp. over a period time

Clustering the countries for quantifying the status of Covid-19 through time series analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Madurapperumage Erandathi ◽  
William Yu Chung Wang ◽  
Chih-Chia Hsieh
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Financial Stability ◽  
Health Facilities ◽  
Safety Measures ◽  
Content Type ◽  
Series Analysis ◽  
The World ◽  
The Status ◽  
The Government

Purpose This study aims to use financial stability and health facilities of countries, to cluster them for making a more consensus environment for manifesting the status of Covid-19 in a justifiable manner. The scarcity of the categorisation of the countries of the world in a common platform, and the requirement of manifesting the pandemic status such as Covid-19 in a justifiable manner create the demanding requirement. This study mainly focusses on assisting to generate a liable manifesto to criticise the span of viral infection of the severe acute respiratory syndrome coronavirus-2 over the globe. Design/methodology/approach Data for this study has been gathered from official websites of the World Bank, and the world in data. The Louvain clustering method has been used to cluster the countries based on their financial strength and health facilities. The resulted clusters are visualised using Silhouette plots. The anomalies of the clusters had been used to quantify the pandemic situation. The status of Covid-19 has been manifested with the time series analysis through python programming. Findings The countries of the world have been clustered into seven, where developed countries divided into three clusters and the countries with transition economies and developing clustered together into four clusters. The time series analysis of recognised anomalies of the clusters assist to monitor the government responses and analyse the efficiency of used safety measures against the pandemic. Originality/value This study’s resulted clusters are highly valuable as a division of countries of the whole world for evaluating the health systems and for the regional levels. Further, the results of time series analysis are beneficial in monitoring the government responses and analysing the efficiency of used safety measures against the pandemic.

Non-Linear Properties of the VIX Index

2017 ◽  
Vol 5 (2) ◽  
pp. 16-24
Author(s):  
L. Magafas ◽  
M. Hanias ◽  
A. Tavlatou ◽  
P. Kostantaki
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Strange Attractor ◽  
Series Analysis ◽  
The World ◽  
Non Linear ◽  
The Future ◽  
Stock Indexes

This paper applies non-linear methods to analyze and predict the daily VIX index which is one of the most important stock indexes in the world. The aim of the analysis is to quantitatively show if the corresponding time series is a deterministic chaotic one and if one or more days ahead prediction can be achieved. The research employs Grassberger and Procaccia's methodology in the time series analysis in order to estimate the correlation and minimum embedding dimensions of the corresponding strange attractor. To achieve from the sample a multistep ahead prediction, the article gives the average for overall neighbours' projections of k-steps into the future. These results make the present work a valuable tool for traders, investors, and funds.

scholarly journals ANALYSIS OF INCIDENCES OF COLLAPSED BUILDINGS IN LAGOS METROPOLIS, NIGERIA

2010 ◽  
Vol 14 (4) ◽  
pp. 332-346 ◽  
Author(s):  
Ayotunde Olawande Oni
Keyword(s):  
Time Series ◽  
Spatial Analysis ◽  
Time Series Analysis ◽  
High Concentration ◽  
Comprehensive Investigation ◽  
The Past ◽  
Series Analysis ◽  
The Future ◽  
Collapsed Buildings

Building collapses in Lagos metropolis have become worrisome to residents, developers, and Government. This study examined the incidences of collapsed buildings in Lagos metropolis over a thirty‐year period. Time series analysis was carried out to determine the past and predict direction of the future occurrences. In addition, a process of inference from reports on investigations of past occurrences was adopted to establish causes of building collapses in the study area. Spatial analysis of the collapses showed high concentration in swampy terrain that was reclaimed in the past. The study recommends, amongst other things, comprehensive investigation of the geophysical characteristics of the affected locations towards finding lasting solution to the menace. Santruka Lagose griūvantys pastatai kelia nerima gyventojams, vystytojams ir vyriausybei. Šiame tyrime nagrinejamas pastatu griuvumo dažnumas Lagose per trisdešimt metu. Atlikta laiko eilučiu analize, siekiant nustatyti buvusius atvejus ir numatyti būsimu atveju tendencijas. Be to, siekiant nustatyti, del kokiu priežasčiu tiriamoje teritorijoje griūva pastatai, buvo pasirinktas išvadu procesas, pagristas ankstesniu atveju tyrimo ataskaitomis. Erdvine griuvimu analize parode didele koncentracija pelketose vietovese, kurios anksčiau buvo melioruotos. Be kitu dalyku, tyrime rekomenduojama atlikti išsamu paveiktu vietoviu geofiziniu savybiu tyrima, siekiant rasti ilgalaiki sprendima, kaip išvengti šios gresmes.

scholarly journals Application of Time-Series Analysis for Predicting Defects in Continuous Steel Casting Process

2016 ◽  
Vol 16 (4) ◽  
pp. 125-130
Author(s):  
A. Rodziewicz ◽  
M. Perzyk
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Steel Casting ◽  
Casting Process ◽  
Continuous Steel Casting ◽  
Continuous Steel ◽  
Industrial Data ◽  
The Real ◽  
Series Analysis ◽  
The Future

Abstract The purpose of this paper was testing suitability of the time-series analysis for quality control of the continuous steel casting process in production conditions. The analysis was carried out on industrial data collected in one of Polish steel plants. The production data concerned defective fractions of billets obtained in the process. The procedure of the industrial data preparation is presented. The computations for the time-series analysis were carried out in two ways, both using the authors’ own software. The first one, applied to the real numbers type of the data has a wide range of capabilities, including not only prediction of the future values but also detection of important periodicity in data. In the second approach the data were assumed in a binary (categorical) form, i.e. the every heat(melt) was labeled as ‘Good’ or ‘Defective’. The naïve Bayesian classifier was used for predicting the successive values. The most interesting results of the analysis include good prediction accuracies obtained by both methodologies, the crucial influence of the last preceding point on the predicted result for the real data time-series analysis as well as obtaining an information about the type of misclassification for binary data. The possibility of prediction of the future values can be used by engineering or operational staff with an expert knowledge to decrease fraction of defective products by taking appropriate action when the forthcoming period is identified as critical.

Sign in / Sign up

Export Citation Format

Share Document