The Technological Diffusion as a Dimension of the Link Between Exports, Imports, and Growth in Tunisia

2019 ◽  
Vol 8 (3) ◽  
pp. 37-55
Author(s):  
Amene Khalifa
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Positive Impact ◽  
The Other ◽  
Technological Diffusion ◽  
Technological Spillovers ◽  
Series Analysis ◽  
Extensive And Intensive Margins ◽  
Level Data ◽  
Manufactured Exports

This paper is an exploration of the technological dimension that shapes the link between intermediate and capital goods imports (IKGM), manufactured exports (MX), and growth in the case of Tunisia. Within a time series analysis (1970-2016), the author focuses on the extent to which these two components of trade are differentiated and therefore incorporating increasing technological content. By using three-digit SITC-level data of IKGM and of MX, it is shown that weighing simple measures of exports and of imports with a measure of their differentiation reveals that exports are sufficiently differentiated to ensure technological spillovers, on one hand, and the payment of IKGM, on the other hand. The extensive and intensive margins of trade are also explored from the sides of exports and imports. They are put in evidence given the positive impact on growth of IKGM and MX measured in accordance to their differentiated configuration.

scholarly journals Effect of tobacco control policies on the Swedish smoking quitline using intervention time-series analysis

BMJ Open ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. e033650
Author(s):  
Xingwu Zhou ◽  
Alessio Crippa ◽  
Anna-Karin Danielsson ◽  
Maria R Galanti ◽  
Nicola Orsini
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Passive Smoking ◽  
Transfer Functions ◽  
Positive Impact ◽  
Calendar Time ◽  
Series Analysis ◽  
Phone Calls ◽  
Pictorial Warnings ◽  
Tobacco Tax

ObjectivesTo coherently examine the responsiveness of the Swedish National Tobacco Quitline (SNTQ) to different types of anti-smoking policies over an extended period of calendar time.DesignQuasi-experimental design with an intervention time-series analysis based on 19 years series of data collected between January 1999 and August 2017 (224 months). Statistical inference on calling rates and rate ratios was obtained using intervention time-series models (Poisson regression and transfer functions).ParticipantsA total of 179 851 phone calls to the SNTQ.InterventionsRecent application of the 2014/40/ European Union (EU) Tobacco Products Directive in 2016. Historical interventions such as a campaign on passive smoking in January 2001; introduction of larger text warnings on cigarette packages since September 2002; banning smoking in restaurants since June 2005; and tobacco tax increase by 10% since January 2012.Outcome measureCalling rates to the SNTQ expressed per 100 000 smokers.SettingSweden.ResultsThe introduction of large pictorial warnings together with text warnings on cigarette packages (May 2016) was associated with a 35% increase in SNTQ calling rate (95% CI 1.16 to 1.57). The campaign on passive smoking (Jan 2001) was associated with a 61% higher calling rate (95% CI 1.06 to 2.45). Larger text warnings on cigarette packs (Sept 2002) conferred a 28% increment in the calling rate (95% CI 1.15 to 1.42); and prohibition to smoke in restaurants (Jun 2005) was associated with a 15% increase in the calling rate (95% CI 1.01 to 1.30). The 10% tobacco tax increase (Jan 2012) was associated with a 3% higher calling rate (95% CI 0.90 to 1.19).ConclusionsWithin an overall decreasing trend of daily smoking in Sweden, we found that the recent introduction of pictorial warnings together with text warnings and referral text had a discernible positive impact on the calling rates to the smoking quitline. We were also able to detect a likely impact of earlier nationwide interventions.

scholarly journals INTERACTION BETWEEN THE ECONOMIC GROWTH AND THE CONSTRUCTION INDUSTRY: A TIME SERIES ANALYSIS ON TURKEY (2000-2012)

2013 ◽  
Vol 3 (1) ◽  
pp. 20-34 ◽  
Author(s):  
Bilal Kargı
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Analysis ◽  
Construction Industry ◽  
Developed Countries ◽  
The Other ◽  
Gdp Growth ◽  
Quarterly Data ◽  
Series Analysis ◽  
Gdp Growth Rate

In this study the relation between the economic growth and the construction industry has been tackled. While the growth the rate of the construction industry in the developing countries is more than the GDP growth rate, it is detected that the percent age it takes in the GDP of developed countries relatively diminishes. On the other hand the construction industry’s growth in the economic fluctuation periods, in the aftermath of a recession, is more than the GDP. These two proposals are tested by the quarterly data of 2000:01-2012:03 for Turkey. Additionally the relation between the economic growth and the construction industry is subjected to the Granger causality test.Keywords: Economic growth, construction industry, time series analysis.

scholarly journals Impact of the Expert Consensus on Carbapenem Consumption Trends and Patterns in Public Healthcare Institutes: An Interrupted Time Series Analysis, 2017–2020

2022 ◽  
Vol 12 ◽  
Author(s):  
Dan Ye ◽  
Caijun Yang ◽  
Wenjing Ji ◽  
Jie Zheng ◽  
Jingyi Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Positive Impact ◽  
Interrupted Time Series ◽  
Expert Consensus ◽  
Shaanxi Province ◽  
Public Healthcare ◽  
Interrupted Time Series Analysis ◽  
Series Analysis

Background: Carbapenems are considered the last line of defence against bacterial infections, but their high consumption and the resulting antibacterial resistance are an increasing global concern. In this context, the Chinese health authority issued an expert consensus on the clinical applications of carbapenems. However, the long- and short-term effects of the expert consensus on carbapenem use are not clear.Methods: This study was conducted in Shaanxi, a northwest province of China. We collected all available carbapenem procurement data between January 2017 and December 2020 from the Provincial Drug Centralized Bidding Procurement System. A quasi-experimental interrupted time series analysis was used to evaluate the longitudinal effectiveness of expert consensus by measuring the change in the Defined Daily Dosesper 1,000 inhabitants per day (DID), the percentage of carbapenem expenditures to total antimicrobial expenditure, the total carbapenem expenditure, and the defined daily cost (DDDc). We used Stata SE version 15.0 for data analysis, and p < 0.05 was considered statistically significant.Results: After the distribution of the expert consensus, the level (p = 0.769) and trend (p = 0.184) of DID decreased, but the differences were not statistically significant. The percentage of carbapenem expenditures to total antimicrobial expenditure decreased abruptly (p < 0.001) after the intervention, but the long-term trend was still upward. There was no statistically significant relationship between the release of the expert consensus and carbapenem expenditure in the long term, but there was a decreasing trend (p = 0.032). However, the expert consensus had a positive impact on the economic burden of carbapenem usage in patients, as the level (p < 0.001), and trend (p = 0.003) of DDDc significantly decreased.Conclusion: The long-term effects of the distribution of the expert consensus on the use and expenditure of carbapenems in public health institutions in Shaanxi Province were not optimal. It is time to set up more administrative measures and scientific supervision to establish a specific index to limit the application of carbapenems.

scholarly journals Handling Missing Values in Interrupted Time Series Analysis of Longitudinal Individual-Level Data

2020 ◽  
Vol Volume 12 ◽  
pp. 1045-1057
Author(s):  
Juan Carlos Bazo-Alvarez ◽  
Tim P Morris ◽  
Tra My Pham ◽  
James R Carpenter ◽  
Irene Petersen
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Missing Values ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Individual Level ◽  
Series Analysis ◽  
Level Data

scholarly journals Nexus between Economic Growth, Tourism Revenue and Financial Development in Bangladesh: A Time Series Analysis

2019 ◽  
Vol 9 (3) ◽  
pp. 134
Author(s):  
Syeda Sumaiya Habib ◽  
Md. Shahanawaz Sharif ◽  
Mohammad Amzad Hossain
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Analysis ◽  
Financial Development ◽  
Positive Impact ◽  
Series Data ◽  
Series Analysis ◽  
Long Run ◽  
Short Run ◽  
Tourism Revenue

The main objective of this study is to analyze the nexus between economic growth, tourism revenue, and financial development in Bangladesh. This paper uses time series data from 1995 to 2016. Advance technique of time series analysis: Johansen Cointegration Approach is used to test the Cointegration among variables. Moreover, the Vector Error Correction (VECM) has been applied to study the long run and short run association among variables. The outcome of this study reveals that the tourism revenue and financial development has positive impact on economic growth in the long run. Variance decomposition and impulse response function also supports the positive association. According to the estimation of Granger Causality also reveals the unilateral direction in short run economic growth to tourism revenue. Providing more credit by financial sector to invest more on infrastructure and promoting Bangladesh as well as insuring proper security for foreign visitors would increase the revenue of this sector, which in turn stimulates economic growth of the country.

scholarly journals Impact of Construction IT Technology Convergence Innovation on Business Performance

2018 ◽  
Vol 10 (11) ◽  
pp. 3972 ◽  
Author(s):  
Dae Kim ◽  
Sang Choi
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Production Process ◽  
Business Performance ◽  
Industrial Revolution ◽  
Positive Impact ◽  
Analysis Data ◽  
Series Analysis ◽  
It Innovation ◽  
The Impact

As the era of the fourth Industrial revolution begins, there is high demand for new information technology (IT) innovation to address the challenges of a dramatically changing industrial landscape. The construction industry, which is one the most important traditional industries in Korea, has adopted new IT innovation in their products to meet customer demand, regulation from government, energy efficiency, security, and so on. The aim of our study is to empirically clarify the impact of technology innovation on the business performance for Korean domestic construction conglomerates. The study performs an empirical analysis with time series analysis on business performance from the perspective of client satisfaction with the services the target companies provide and the production process improvement, as well as from a financial perspective. As analysis data, statistical data from the Ministry of Science, ICT, and Future Planning; Brand Stock; Bank of Korea; and each company are utilized, and the target companies for our study are limited to 19 construction companies with an apartment brand. Multiple regression analysis is used as a fundamental analysis methodology of our study. For Time Series Analysis, the Box Jenkins Model, namely, ARIMA is utilized. According to our results, it is found that any improvement of IT convergence innovation competence such as business efficiency IT index, collaboration IT index, and strategy management IT index has a positive impact on the production process, financial performance, and customer satisfaction with the services the companies provide.

Accuracy Validation of Flood Forecasting Method Based on Time Series Analysis Using Observed Water Level and Rainfall Data

2020 ◽  
Author(s):  
Naoki Koyama ◽  
Tadashi Yamada
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Water Level ◽  
First Grade ◽  
Flood Forecasting ◽  
Rainfall Data ◽  
Flood Prediction ◽  
Series Analysis ◽  
Level Data ◽  
Water Level Data

<p>The aim of this paper is to verify the accuracy of the real-time flood prediction model, using the time-series analysis. Forecast information of water level is important information that encourages residents to evacuate. Generally, flood forecasting is conducted by using runoff analysis. However, in developing countries, there are not enough hydrological data in a basin. Therefore, this study assumes where poor hydrologic data basin and evaluates it through reproducibility and prediction by using time series analysis which statistical model with the water level data and rainfall data. The model is applied to the one catchment of the upper Tone River basin, one of the first grade river in Japan. This method is possible to reproduce hydrograph, if the observation stations exist several points in the basin. And using the estimated parameters from past flood events, we can apply this method to predict the water level until the flood concentration time which the reference point and observation station. And until this time, the peak water level can be predicted with the accuracy of several 10cm. Prediction can be performed using only water level data, but by adding rainfall data, prediction can be performed for a longer time.</p>

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