scholarly journals INSURANCE AND ECONOMIC DEVELOPMENT IN NIGERIA: CO-INTEGRATION AND CAUSALITY ANALYSIS

2017 ◽  
Vol 4 (4) ◽  
pp. 28 ◽  
Author(s):  
Mfon Sampson Ukpong ◽  
Ikechukwu A. Acha
Keyword(s):  
Time Series ◽  
Economic Development ◽  
Causal Relationship ◽  
Life Insurance ◽  
Time Series Data ◽  
Series Data ◽  
Insurance Premiums ◽  
Stationarity Test ◽  
Total Life

We examine the cointegration and causal relationship between insurance and economic development in Nigeria using time series data from 1990 – 2013. Gross domestic product (GDP) is adopted as a proxy for the level of economic development, while total life insurance premiums (TPL), total non-life insurance premiums (TPNL) and total insurance investment (TII) are used in measuring growth in the insurance sector. Data is operationalized through the stationarity test, cointegration test, regression analysis and granger causality tests. The stationarity test reveals that all-time series data are stationary at the 1%, 5% and 10% levels of significance. The test for cointegration shows that all cointegrate when GDP is the endogenous variable. The granger causality test reveals that there is a bidirectional relationship existing between GDP and total non-life insurance premiums while a unidirectional relationship exists between GDP and total life insurance premiums with no causal relationship existing between GDP and total insurance investments. An R-squared value of 0.9776 indicates that the independent variables account for 97.8% of the variations in GDP while the remaining 2.2% is attributable to influence of other variables or fators not in the scope of this study. We conclude that insurance not only contributes to economic development but also has a long term equilibrium relationship. Therefore, we recommend that insurance activities in the country should be encouraged to promote effectiveness and efficiency in order to enhance the long term relationship with economic development.

scholarly journals Growth Effects of Remittance: A Case of Turkey Diaspora

2021 ◽  
Vol 58 (1) ◽  
pp. 690-698
Author(s):  
Dr. Caterina De Lucia Et al.
Keyword(s):  
Time Series ◽  
Economic Development ◽  
Time Series Data ◽  
Developing Economies ◽  
Human Life ◽  
Economic Indicator ◽  
Series Data ◽  
World Economic ◽  
The Government

In the age of globalization, remittances are an essential part of human life. This analysis's key objective is to examine the effect of remittances in developing economies like Turkey on economic development. The 1980 to 2020 time-series data used in this analysis which use numerous time series estimating techniques. Sending data is given by the Banks of Turkey and in a million dollars. Simultaneously, economic development or GDP data are provided by world economic indicator, the World Bank, and the new US dollar. The findings indicated that there are both short-term and long-term ties between transactions and economic development in Turkey. Therefore, results indicate that Turkey's transition flows positively affect Turkey's person and Turkey's macroeconomic scenario. The government should implement policies that allow Turkey in overseas countries to submit transmissions through official channels.

scholarly journals Assessing Stream-Aquifer Connectivity in a Coastal California Watershed

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 416
Author(s):  
Bwalya Malama ◽  
Devin Pritchard-Peterson ◽  
John J. Jasbinsek ◽  
Christopher Surfleet
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Water Level ◽  
Time Series Data ◽  
Series Data ◽  
Low Permeability ◽  
Pumping Tests ◽  
Stream Flows ◽  
The Impact

We report the results of field and laboratory investigations of stream-aquifer interactions in a watershed along the California coast to assess the impact of groundwater pumping for irrigation on stream flows. The methods used include subsurface sediment sampling using direct-push drilling, laboratory permeability and particle size analyses of sediment, piezometer installation and instrumentation, stream discharge and stage monitoring, pumping tests for aquifer characterization, resistivity surveys, and long-term passive monitoring of stream stage and groundwater levels. Spectral analysis of long-term water level data was used to assess correlation between stream and groundwater level time series data. The investigations revealed the presence of a thin low permeability silt-clay aquitard unit between the main aquifer and the stream. This suggested a three layer conceptual model of the subsurface comprising unconfined and confined aquifers separated by an aquitard layer. This was broadly confirmed by resistivity surveys and pumping tests, the latter of which indicated the occurrence of leakage across the aquitard. The aquitard was determined to be 2–3 orders of magnitude less permeable than the aquifer, which is indicative of weak stream-aquifer connectivity and was confirmed by spectral analysis of stream-aquifer water level time series. The results illustrate the importance of site-specific investigations and suggest that even in systems where the stream is not in direct hydraulic contact with the producing aquifer, long-term stream depletion can occur due to leakage across low permeability units. This has implications for management of stream flows, groundwater abstraction, and water resources management during prolonged periods of drought.

Welfare Use in Japan: Trends and Determinants

2007 ◽  
pp. 88
Author(s):  
Wataru Suzuki ◽  
Yanfei Zhou
Keyword(s):  
Time Series ◽  
Longitudinal Data ◽  
Time Series Data ◽  
Positive Impact ◽  
Series Data ◽  
Negative Effects ◽  
Long Time ◽  
Welfare Use ◽  
The Impact

This article represents the first step in filling a large gap in knowledge concerning why Public Assistance (PA) use recently rose so fast in Japan. Specifically, we try to address this problem not only by performing a Blanchard and Quah decomposition on long-term monthly time series data (1960:04-2006:10), but also by estimating prefecturelevel longitudinal data. Two interesting findings emerge from the time series analysis. The first is that permanent shock imposes a continuously positive impact on the PA rate and is the main driving factor behind the recent increase in welfare use. The second finding is that the impact of temporary shock will last for a long time. The rate of the use of welfare is quite rigid because even if the PA rate rises due to temporary shocks, it takes about 8 or 9 years for it to regain its normal level. On the other hand, estimations of prefecture-level longitudinal data indicate that the Financial Capability Index (FCI) of the local government2 and minimum wage both impose negative effects on the PA rate. We also find that the rapid aging of Japan's population presents a permanent shock in practice, which makes it the most prominent contribution to surging welfare use.

CAUSAL RELATIONSHIP OF ENERGY CONSUMPTION AND ECONOMIC GROWTH – A CASE STUDY OF PAKISTAN

2021 ◽  
Vol 9 (1) ◽  
pp. 139-164
Author(s):  
Saddam Hussain ◽  
Chunjiao Yu
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Energy Consumption ◽  
Causal Relationship ◽  
Inflation Rate ◽  
Time Series Data ◽  
Consumer Price Index ◽  
Series Data ◽  
Relationship Of

This paper explores the causal relationship between energy consumption and economic growth in Pakistan, applying techniques of co-integration and Hsiao’s version of Granger causality, using time series data over the period 1965-2019. Time series data of macroeconomic determi-nants – i.e. energy growth, Foreign Direct Investment (FDI) growth and population growth shows a positive correlation with economic growth while there is no correlation founded be-tween economic growth and inflation rate or Consumer Price Index (CPI). The general conclu-sion of empirical results is that economic growth causes energy consumption.

scholarly journals Prediction of Urban and Rural Tourism Economic Forecast Based on Machine Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Wusheng Zhou
Keyword(s):  
Time Series ◽  
Economic Development ◽  
Causal Relationship ◽  
Local Economic Development ◽  
Tourism Industry ◽  
Local Economy ◽  
Series Data ◽  
Economic Forecast ◽  
The Relationship ◽  
Tourism Revenue

With the rapid development of tourism, tourism revenue, as one of the important indicators to measure the development of the tourism economy, has high research value. The quasi-prediction of tourism revenue can drive the development of a series of related industries and accelerate the development of the domestic economy. When forecasting tourism income, it is necessary to examine the causal relationship between tourism income and local economic development. The traditional cointegration analysis method is to extract the promotion characteristics of tourism income to the local economy and construct a tourism income prediction model, but it cannot accurately describe the causal relationship between tourism income and local economic development and cannot accurately predict tourism income. We propose an optimized forecasting method of tourism revenue based on time series. This method first conducts a cointegration test on the time series data of the relationship between tourism income and local economic development, constructs a two-variable autoregressive model of tourism income and local economy, and uses the swarm intelligence method to test the causal relationship and the relationship between tourism income and local economic development, calculate the proportion of tourism industry, define the calculation result as the direct influence factor of tourism industry on the local economy, calculate the relevant effect of local tourism development and economic income, and construct tourism income optimization forecast model. The simulation results show that the model used can accurately predict tourism revenue.

scholarly journals Minimum time required to detect population trends: the need for long-term monitoring programs

2017 ◽  
Author(s):  
Easton R White
Keyword(s):  
Time Series ◽  
Statistical Power ◽  
Time Series Data ◽  
Conservation Status ◽  
Monitoring Program ◽  
Minimum Time ◽  
Series Data ◽  
Series Length ◽  
Time Required

Long-term time series are necessary to better understand population dynamics, assess species' conservation status, and make management decisions. However, population data are often expensive, requiring a lot of time and resources. When is a population time series long enough to address a question of interest? We determine the minimum time series length required to detect significant increases or decreases in population abundance. To address this question, we use simulation methods and examine 878 populations of vertebrate species. Here we show that 15-20 years of continuous monitoring are required in order to achieve a high level of statistical power. For both simulations and the time series data, the minimum time required depends on trend strength, population variability, and temporal autocorrelation. These results point to the importance of sampling populations over long periods of time. We argue that statistical power needs to be considered in monitoring program design and evaluation. Time series less than 15-20 years are likely underpowered and potentially misleading.

scholarly journals PENGARUH ZIS (ZAKAT, INFAK, SEDEKAH) DAN ZAKAT FITRAH TERHADAP PENURUNAN KEMISKINAN DI INDONESIA PERIODE 1998 - 2010

Media Ekonomi ◽  
2017 ◽  
Vol 20 (1) ◽  
pp. 83
Author(s):  
Jumadin Lapopo
Keyword(s):  
Time Series ◽  
Developing Countries ◽  
Regression Analysis ◽  
Poverty Reduction ◽  
Time Series Data ◽  
Secondary Data ◽  
Series Data ◽  
Analysis Model ◽  
Independent Variables

<p>Poverty is being a problem in all developing countries including Indonesia. Among goverment programs, poverty has become the center offattention in policy at both of the regional and national levels. Looking at thephenomenon of poverty, Islam present with solution to reduce poverty through Zakat. This study aims to analyze the effect of ZIS and Zakat Fitrah against poverty in Indonesia in 1998 until 2010, data used in this study is secondary data and uses time series data, for the dependent variabel is poverty and for independent variables are ZIS and Zakat Fitrah. The analysis tools used in this study is to use multiple regression analysis model and the assumptions of classical test using the software Eviews-4. In this study also concluded that the ZIS variables significantly affect to the reduction of poverty in Indonesia although the effect is very small. In the variable Zakat Fitrah not significantly affect poverty reduction in Indonesia because of the nature of Zakat Fitrah is for consumption and not for long-term needs. The results of this study can be used for the management of zakat to be able to develop the management and to get a better system for distribution of zakat so that the main purpose of zakat can be achieved to reduce poverty.<br />Keywords : Poverty, Zakat Fitrah, ZIS.</p>

scholarly journals Track Irregularity Time Series Analysis and Trend Forecasting

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Jia Chaolong ◽  
Xu Weixiang ◽  
Wang Futian ◽  
Wang Hanning
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Short Term ◽  
Measuring Point ◽  
Trend Forecasting ◽  
Changing Trend ◽  
Track Irregularity ◽  
Linear Differential

The combination of linear and nonlinear methods is widely used in the prediction of time series data. This paper analyzes track irregularity time series data by using gray incidence degree models and methods of data transformation, trying to find the connotative relationship between the time series data. In this paper, GM(1,1)is based on first-order, single variable linear differential equations; after an adaptive improvement and error correction, it is used to predict the long-term changing trend of track irregularity at a fixed measuring point; the stochastic linear AR, Kalman filtering model, and artificial neural network model are applied to predict the short-term changing trend of track irregularity at unit section. Both long-term and short-term changes prove that the model is effective and can achieve the expected accuracy.

Sign in / Sign up

Export Citation Format

Share Document