scholarly journals Investigating changes over time of annual rainfall in Zimbabwe

2010 ◽  
Vol 14 (12) ◽  
pp. 2671-2679 ◽  
Author(s):  
D. Mazvimavi
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Quantile Regression ◽  
Rainy Season ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Average Rainfall ◽  
Quantile Regression Analysis ◽  
Changes Over Time ◽  
Over Time

Abstract. There is increasing concern in southern Africa about the possible decline of rainfall as a result of global warming. Some studies concluded that average rainfall in Zimbabwe had declined by 10% or 100 mm during the last 100 years. This paper investigates the validity of the assumption that rainfall is declining in Zimbabwe. Time series of annual rainfall, and total rainfall for (a) the early part of the rainy season, October-November-December (OND), and (b) the mid to end of the rainy season, January-February-March (JFM) are analysed for the presence of trends using the Mann-Kendall test, and for the decline or increase during years with either high or low rainfall using quantile regression analysis. The Pettitt test has also been utilized to examine the possible existence of change or break-points in the rainfall time series. The analysis has been done for 40 rainfall stations with records starting during the 1892–1940 period and ending in 2000, and representative of all the rainfall regions. The Mann-Kendal test did not identify a significant trend at all the 40 stations, and therefore there is no proof that the average rainfall at each of these stations has changed. Quantile regression analysis revealed a decline in annual rainfall less than the tenth percentile at only one station, and increasing of rainfall greater than the ninetieth percentile at another station. All the other stations had no changes over time in both the low and high rainfall at the annual interval. Climate change effects are therefore not yet statistically significant within time series of total seasonal and annual rainfall in Zimbabwe. The general perception about declining rainfall is likely due to the presence of multidecadal variability characterized by bunching of years with above (e.g. 1951–1958, 1973–1980) and below (e.g. 1959–1972, 1982–1994 ) average rainfall.

scholarly journals Investigating possible changes of extreme annual rainfall in Zimbabwe

2008 ◽  
Vol 5 (4) ◽  
pp. 1765-1785 ◽  
Author(s):  
D. Mazvimavi
Keyword(s):  
Global Warming ◽  
Regression Analysis ◽  
Water Resources ◽  
Quantile Regression ◽  
Rainy Season ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Management Approach ◽  
Average Rainfall ◽  
Quantile Regression Analysis

Abstract. There is increasing concern about the perceived decline in rainfall which is sometimes attributed to global warming. Some studies have concluded that average rainfall in Zimbabwe has declined by 10% or 100 mm/yr during the last 100 yrs. This paper investigates the validity of the assumption that rainfall is declining in Zimbabwe. Time series of annual rainfall, and total rainfall for a) the early party of the rainy season, October-November-December (OND), and b) the mid to end of the rainy season, January-February-March (JFM) are analysed for the presence of trends using the Mann-Kendall test, and changes in extreme rainfall using quantile regression analysis. The analysis has been done for 40 rainfall stations with records starting during the 1892–1940 period and ending in 2000, and representative of the major rainfall regions. The Mann-Kendal test did not identify a significant trend at all the 40 stations, and therefore there is no proof that the average rainfall at each of these stations has changed. Quantile regression analysis revealed a decline in annual rainfall less than the tenth percentile at only one station, and increasing rainfall for rainfall greater than the ninetieth percentile at another station. All the other stations revealed no changes over time in both the extreme low and high rainfall at the annual interval. Therefore, there is no evidence that the frequency and severity of droughts has changed during the 1892 to 2000 period. The general perception about declining rainfall is likely shaped by a comparison of the recent drought years (1980's–1990's) to recent wet periods (1970's). There have however been periods with similar dry years beyond the recallable memory, e.g. 1926–1936, 1940's. Crop failures and livestock losses attributed to declining rainfall are most likely due to poor agricultural practices such as production of crops in unsuitable climatic regions, degradation of rangelands partly due to increasing livestock populations. Rainfall in Zimbabwe has high inter-annual variability, and currently any change due to global warming is not yet statistically detectable. The annual renewal rate of water resources from rainfall has therefore not changed, and an adaptive water resources management approach is called to overcome problems arising from increasing water demand, and variability of available water resources.

Spatiotemporal variability of annual and seasonal rainfall time series in Ho Chi Minh city, Vietnam

2018 ◽  
Vol 10 (3) ◽  
pp. 658-670 ◽  
Author(s):  
Dang Nguyen Dong Phuong ◽  
Vu Thuy Linh ◽  
Tran Thong Nhat ◽  
Ho Minh Dung ◽  
Nguyen Kim Loi
Keyword(s):  
Time Series ◽  
Rainy Season ◽  
Kendall Test ◽  
Dry Season ◽  
Seasonal Rainfall ◽  
Spatiotemporal Variability ◽  
Ho Chi Minh City ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Spatial And Temporal Patterns

Abstract This study analyzed spatial and temporal patterns of rainfall time series from 14 proportionally distributed stations in Ho Chi Minh City for the period 1980–2016. Both parametric and nonparametric approaches, specifically, linear regression, the Mann–Kendall test and Sen's slope estimator, were applied to detect and estimate the annual and seasonal trends after using original and notched boxplots for the preliminary interpretation. The outcomes showed high domination of positive trends in the annual and seasonal rainfall time series over the 37-year period, but most statistically significant trends were observed in the dry season. The results of trend estimation also indicated higher increasing rates of rainfall in the dry season compared to the rainy season at most stations. Even though the total amount of annual rainfall is mainly contributed by rainfall during the rainy season, the pronounced increment in the dry season can be a determining factor of possible changes in annual rainfall. Additionally, the interpolated results revealed a consistently increasing trend in the southeastern parts of the study area (i.e., Can Gio district), where annual rainfall was by far the lowest intensity compared to other regions.

scholarly journals Association between leukocyte telomere length and sex by quantile regression analysis

2021 ◽  
Author(s):  
Fernanda Gutierrez-Rodrigues ◽  
Raquel M. Alves-Paiva ◽  
Natália F. Scatena ◽  
Edson Z. Martinez ◽  
Priscila S. Scheucher ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Quantile Regression ◽  
Telomere Length ◽  
Leukocyte Telomere Length ◽  
Quantile Regression Analysis

Determinants of liquidity in Malaysian SMEs: a quantile regression approach

2018 ◽  
Vol 67 (9) ◽  
pp. 1566-1584 ◽  
Author(s):  
Shaista Wasiuzzaman
Keyword(s):  
Regression Analysis ◽  
Quantile Regression ◽  
Emerging Market ◽  
Developed Countries ◽  
Data Availability ◽  
Firm Level ◽  
Liquidity Management ◽  
Ols Regression ◽  
Content Type ◽  
Quantile Regression Analysis

PurposeThe management of liquidity has always been seen as a critical but often ignored issue in finance. Despite the abundance of studies on liquidity management, these studies mainly focus on developed countries and on large firms. Liquidity is critical for the small firm but studies on liquidity management in small and medium enterprises (SMEs) are lacking. The purpose of this paper is to examine the firm-level determinants of liquidity of SMEs in Malaysia.Design/methodology/approachData are collected for a total of 986 small firms in Malaysia from 2011 to 2014, resulting in a total of 2,683 observations. Firm-specific variables and the effect of the economy are considered as the possible determinants of liquidity. Ordinary least squares (OLS) regression analysis with standard errors adjusted for firm-level clustering and quantile regression analysis are used for this purpose.FindingsAnalysis using OLS regression technique indicates that a firm’s profitability, its growth, asset tangibility, size, age and firm status are significant factors in influencing its liquidity decision. Leverage and economic condition are not found to have any significant influence on liquidity. However, quantile regression analysis provides a different picture especially for SMEs with liquidity at the quantile levels ofθ=0.10 and 0.90. Atθ=0.10, only profitability, tangibility and firm status are significant, while atθ=0.90, tangibility, size, firm status and, to some extent, age are significant in influencing liquidity levels.Originality/valueTo the author’s knowledge, this is the first study analyzing the liquidity decision of SMEs in an emerging market such as Malaysia. Most studies on liquidity management of SMEs are focused on developed countries due to data availability but these studies are also only a handful. Additionally, this study uses quantile regression analysis which highlights the need to analyze financial decisions at different levels rather than at the aggregate level as done in OLS regression analysis.

Income Elasticities for State Tax Revenues: Techniques of Estimation and Their Usefulness for Forecasting

1973 ◽  
Vol 1 (4) ◽  
pp. 409-425 ◽  
Author(s):  
Robert E. Berney ◽  
Bernard H. Frerichs
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Income Elasticity ◽  
Income Elasticities ◽  
Tax Revenues ◽  
State Tax ◽  
The Stability ◽  
Revenue Estimation ◽  
Theoretical Foundations ◽  
Over Time

The concept of income elasticity of tax revenues has been used in numerous studies with little concern about its theoretical foundations. Income elasticities have also been used for revenue estimation with limited concern about stability over time or about the accuracy of the forecasts. This paper explores the development of the tax elasticity measure and, using revenue data from Washington, compares year-to-year elasticity measures with those established by regression analysis. The length of the time series is varied to check on the stability of the coefficients. Finally, the elasticities are used to predict revenues for three years to check on their accuracy for revenue estimation.

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